Azure DevOps MCP Server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation4/5
Most tools are clearly separated by resource (work items, boards, iterations, PRs, teams, repos, wikis), but some overlap exists within work items (e.g., azure_get_work_item vs azure_query_work_items vs azure_get_my_tasks). Helpers like get_my_tasks and get_critical_bugs are essentially specialized queries, which could cause slight confusion.
Naming Consistency4/5
Tool names generally follow the verb_noun pattern (e.g., azure_create_work_item, azure_list_boards), but there are minor inconsistencies like azure_get_board_config vs azure_update_board (not update_board_config) and azure_get_work_item_states. Overall predictable but not perfectly uniform.
Tool Count2/5
With 30 tools, the server exceeds the recommended range and feels heavy. While it covers multiple Azure DevOps domains, many subdomains have only a few operations, making the high count unnecessary and potentially overwhelming.
Completeness3/5
Work items and wikis have decent lifecycle coverage, but other areas are incomplete: pull requests only support list/create (no get/update/merge), repositories have only list/get (no create/delete), and teams lack update/delete. These gaps will force agents to work around missing functionality.
Average 3.2/5 across 30 of 30 tools scored. Lowest: 2.2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the basic action of creating a pull request, without mentioning side effects, permissions, or any operational characteristics. This is insufficient for an agent to understand the tool's behavior beyond the verb 'create'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. It is front-loaded and appropriately short, though it lacks substantive content. The structure is efficient, but the sentence's tautological nature prevents a higher score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a create operation with 5 parameters and no annotations or output schema, the description is far too minimal. It does not explain the action's prerequisites, effects, or return values, leaving significant gaps in context that a more thorough description should fill.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all five parameters having clear descriptions. The tool description itself adds no parameter information, but the baseline of 3 applies because the schema already documents the parameters thoroughly, making additional description unnecessary.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Cria um novo Pull Request' translates directly to 'Creates a new Pull Request', which merely restates the tool name 'azure_create_pull_request'. It is a tautology, providing no new information about the tool's scope or distinguishing capabilities beyond the name itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, leaving the agent without any decision support for selecting this tool among the many sibling create tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It merely states the action (update settings) without detailing effects, permission requirements, idempotency, or failure modes. This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief, but brevity here results in under-specification rather than efficient structure. It is a single phrase that omits crucial operational details, making it more like a placeholder than a concise, information-dense description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (nested settings object, no output schema, no annotations), the description is severely incomplete. It does not address return values, side effects, or any success/failure indicators, leaving the agent with insufficient information to use the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%, and the tool description adds no parameter-level detail. The 'settings' parameter is a nested object, yet the description gives no insight into what settings are expected or how they map to board configuration. The description fails to compensate for the schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Atualizar configurações de board' clearly communicates an update action on board settings, using a specific verb and resource. While it distinguishes itself from siblings like azure_list_boards or azure_get_board_config by implying a write operation, it does not explicitly differentiate from other update tools in the family.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description does not mention prerequisites, typical use cases, or exclude any scenarios, leaving the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the basic create action and adds no context about required fields, conditional behavior based on 'type', or side effects. The description is too minimal to inform the agent about the tool's behavior beyond the literal action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded and free of fluff. However, it is so brief that it sacrifices informative content, though this is not a conciseness issue but rather a completeness issue.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has five parameters, including a conditional 'type' enum (projectWiki/codeWiki) and fields that are required only for codeWiki. The description provides no context about these variations, no output expectations, and no operational details. With no output schema and no annotations, the description is severely incomplete for the complexity of the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% parameter coverage, with descriptions for all five parameters. The tool description itself adds no new meaning beyond the schema's parameter descriptions, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Cria uma nova wiki no projeto' clearly states the action (create) and resource (wiki) with a project scope. It distinguishes from sibling tools like 'azure_create_wiki_page' by specifying 'wiki' rather than 'wiki page', though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. The description does not mention conditions, prerequisites, or exclude any use cases, leaving the agent to infer usage solely from the tool name and schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It adds nothing beyond the tool name, failing to mention whether the listing is recursive, how filtering works, or any error/edge-case behavior. This is a tautological restatement of the tool's purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but lacks structure. It does not include any additional context or elaboration, making it minimally informative rather than efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with two parameters and no output schema, the description is incomplete. It omits the optional 'path' filter and the scope of the listing (e.g., all pages vs. top-level), leaving the agent with insufficient context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters, so the schema already explains 'path' and 'wikiIdentifier'. The description adds no parameter-specific meaning, but the baseline of 3 is appropriate given full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Lista páginas de uma wiki' clearly identifies the action (list) and resource (pages of a wiki). It is specific enough to distinguish from tools like azure_get_wiki_page, though it does not explicitly mention alternatives or the optional path filter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not explain when to use this tool versus azure_get_wiki_page or other sibling tools, nor does it mention any prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the basic deletion action without mentioning whether deletion is permanent, reversible, requires specific permissions, or what happens if the work item does not exist. This is a significant gap for a destructive operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is appropriately brief for a simple tool, though it could include more context without becoming bloated. The front-loaded verb 'Deleta' immediately conveys the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema and no annotations, the description is under-specified for a mutation tool. It does not explain the return value, error behavior, or any side effects. For a delete operation, one might expect at least a note on permanence or failure modes. The simplicity of the tool (one parameter) is not enough to excuse the lack of context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% parameter description coverage for the single 'id' parameter, so the baseline is 3. The description adds no extra meaning beyond the schema's 'ID do work item a deletar', which is already clear. The description does not compensate or add nuance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Deleta um work item' clearly states the verb (delete) and resource (work item), making the action unambiguous. It differentiates itself from sibling tools like create, update, and get by its destructive nature, so the purpose is clear even without explicit comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when deletion is appropriate, or exclude cases like soft-delete. With many sibling tools, some usage context would be expected but is entirely absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'gets capacity planning' without mentioning what the return data looks like, whether team is required, or any side effects. This is too minimal for transparent behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant words. It is appropriately sized for a simple read operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description should explain what capacity planning includes or return structure. It does not. It also ignores the optional team parameter, leaving the agent without enough context for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters, so the baseline is 3. The description does not add any extra meaning about the parameters (e.g., team optionality or iteration path format), leaving the schema to do all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves capacity planning for an iteration, using a specific verb and resource. It does not explicitly differentiate from sibling tools, but none of the siblings mention capacity planning, so it is implicitly unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks any context about prerequisites, team relevance, or scenarios where this should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It only says 'gets' without clarifying whether content is included by default, what the response structure is, or any potential error behavior. The includeContent parameter hints at content handling, but that information lives in the schema, not the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that immediately conveys the core function. It is front-loaded and contains no unnecessary words, achieving high efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although the tool appears simple, the description lacks essential context. Since there is no output schema, the description should clarify what is returned (e.g., page content, metadata), but it does not. It also fails to explain how this tool differs from related wiki tools, making it incomplete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters with adequate descriptions. The tool description adds no extra meaning or context about how the parameters relate or should be used.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Gets a specific page from the wiki', which clearly indicates the verb and resource. However, it does not explicitly differentiate this from sibling tools like azure_get_wiki or azure_list_wiki_pages, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It lacks any exclusions, prerequisites, or references to sibling tools, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'lists pull requests' and does not explain return format, default status filter, pagination, or any side effects. It is minimally informative beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is appropriately concise for a simple list tool, though it could be slightly more informative while remaining tight.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should explain what the tool returns and any behavioral nuances. It fails to mention the optional 'status' filter or what the response contains, leaving the description incomplete for an agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'repositoryId' and 'status' having descriptions. The tool description itself adds no parameter-specific meaning, so it meets the baseline of 3 without enhancing understanding of how the parameters interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Lista Pull Requests de um repositório' clarifies that the tool lists pull requests for a given repository, using a specific verb and resource. It distinguishes from sibling tools like azure_create_pull_request (create vs list) and azure_list_repositories (repositories vs pull requests). It lacks detail on filtering but is not a tautology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives. There is no mention of prerequisites, contexts, or exclusions. The description only states what it does, not when it should be selected.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure, yet it adds no context: it doesn't state that this is a read-only operation, describe error behavior for invalid WIQL, mention rate limits, or explain what the return payload looks like. The statement merely restates the obvious action of running a query, providing essentially no transparency beyond the verb itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with a clear subject-verb-object structure and zero filler words. It is concise and easy to parse, though its brevity means it forgoes the extra context that would elevate the overall tool documentation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, so the description must explain return behavior and usage context, but it does neither — it doesn't state what the response contains, default fields, pagination via the limit parameter, or when to prefer this over sibling tools. The schema covers parameter semantics well, but the overall description is inadequate for an agent to confidently select and rely on this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% — every parameter (limit, query, fields, fetchDetails) has an inline description, including a WIQL example and the behavioral difference between fetchDetails=true and false. The tool description adds no parameter-level meaning, so per the rubric the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource construction ('Executa uma query WIQL customizada sobre work items' — executes a custom WIQL query on work items), clearly indicating what the tool does. The word 'customizada' (custom) implicitly differentiates it from predefined-query siblings like azure_get_my_tasks and azure_get_critical_bugs, but it doesn't explicitly name those alternatives, keeping it at a 4 rather than a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives—it is a single sentence with no mention of scenarios, prerequisites, or exclusions. Given the 28 sibling tools including predefined query tools (azure_get_my_tasks, azure_get_critical_bugs) and azure_get_work_item, an agent receives no help choosing between them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the basic action, omitting whether updates are partial or full, how unspecified fields are handled, or side effects like relation changes. This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded and easy to parse. It is not overstated, though it could offer more value without violating brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 11 parameters and no output schema or annotations, the description is grossly incomplete. It does not explain update semantics, return values, or prerequisites, leaving the agent without critical context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 82% parameter description coverage, which is high and largely carries the burden. The description itself adds no parameter information, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Atualiza um work item existente' clearly states the tool updates an existing work item, distinguishing it from create/delete/get siblings by the word 'existente'. It is specific about the action and resource, though it does not enumerate what aspects can be updated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like azure_create_work_item or azure_delete_work_item. The description only says 'updates an existing work item', providing no context for selection or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It only warns 'use com cautela,' hinting at destructiveness but failing to specify consequences, reversibility, or impact on dependent items. The description adds minimal transparency beyond an implicit danger signal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence with a parenthetical warning. It is front-loaded with the main action and alerts the user quickly. However, the use of Portuguese in an otherwise English tool name and schema is slightly disorganized, though not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive delete operation with no annotations and no output schema, the description is inadequate. It lacks context about side effects, required permissions, whether the operation is reversible, or what happens to associated work items. The warning is too generic to guide safe usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage for both parameters (team and iterationId) with descriptions, so the baseline is 3. The description adds no additional parameter information, but it does not need to because the schema already explains the fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Deleta uma iteration' (deletes an iteration), using a specific verb and resource. It distinguishes itself from sibling tools like azure_delete_work_item by explicitly targeting iterations, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The warning 'use com cautela' (use with caution) is a generic caution, not a contextual directive. There is no mention of prerequisites, exclusions, or preferred scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It indicates a read operation ('Busca') but does not disclose return format, pagination, default filtering behavior, or the meaning of '(helper)'. Without annotations, this is insufficient for understanding side effects or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the core purpose. It is efficient, though the inclusion of '(helper)' is ambiguous and could be clarified. Overall, it is well-structured and free of redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an input schema, the description is minimally viable but leaves gaps. It lacks information about return values (no output schema), parameter interactions, and the meaning of 'current user' in a multi-tenant context. However, for a basic read operation, it provides adequate initial understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not mention any parameters. With schema coverage at 67% (state and includeCompleted have descriptions, but limit does not), the description adds nothing to clarify parameter usage or the effect of 'limit'. It fails to compensate for the missing 'limit' description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Busca' (searches) with a specific resource ('tasks atribuídas ao usuário atual') and clear scope (current user). This clearly distinguishes it from sibling tools like azure_get_work_item or azure_query_work_items, which target different scopes or queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as azure_query_work_items or azure_get_work_item. It only states what it does, leaving the agent to infer usage context without any explicit 'when to use' or 'when not to use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the basic creation behavior but does not disclose potential side effects, error conditions, authentication requirements, or what happens on path conflicts. This is insufficient for a mutation tool beyond the obvious 'creates'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that communicates the core purpose without any filler or redundancy. It is front-loaded with the verb 'Cria' and clearly names the resource, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and a minimal one-line description, the tool lacks essential context for reliable use. The schema documents parameters but does not explain what the tool returns (if anything), whether an existing wiki identifier is required, or how conflicts are handled. This is inadequate for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so each parameter (wikiIdentifier, path, content) already has a meaningful description. The tool description adds no additional parameter-level detail beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Cria' (creates) and the specific resource 'uma nova página na wiki' (a new wiki page). This precisely conveys the tool's action and distinguishes it from sibling tools like azure_update_wiki_page or azure_list_wiki_pages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no context on when to use this tool versus alternatives. There is no mention of prerequisites (e.g., an existing wiki), nor any exclusions or alternative tool suggestions. The only implied usage is the obvious 'when you need to create a page', which is not explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavior. It indicates a state filter (não concluídos) but does not mention that this is a read-only operation, how results are ordered, or what the output format is. It does not disclose any side effects, authentication needs, or rate limits, leaving the agent with incomplete behavioral knowledge.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the tool's purpose without extraneous words. It is highly concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one optional parameter, no output schema), so a short description can suffice. It names the resource and filter, but it lacks explanation of the parameter and context relative to sibling tools. Given the low complexity, a minimal description is acceptable, but there are clear gaps in parameter documentation and usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter (maxResults) with 0% schema description coverage. The tool description does not mention maxResults at all, nor does it explain its purpose (e.g., limiting the number of results). Since the description is the only source for parameter meaning, this is a significant gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Busca' (searches) and precisely identifies the target: critical bugs (priority 1) that are not completed. This clearly distinguishes it from sibling tools like azure_query_work_items or azure_get_work_item, which are more general. The scope is explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving critical uncompleted bugs, but it does not provide explicit guidance on when to choose this tool over alternatives such as azure_query_work_items. No exclusions or alternative recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that the tool retrieves details but does not explain return format, error behavior, permissions required, or whether it is a read-only operation beyond the inherent meaning of 'get'. This is a minimal disclosure for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that contains no fluff or redundancy. It is front-loaded with the verb and resource, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but there is no output schema and the description leaves the return value ambiguous ('detalhes' is vague). It does not specify whether it returns metadata, content, or something else, and there is no annotation context to fill the gap. This makes it incomplete for an agent to fully understand what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides full documentation for the single parameter (wikiIdentifier: 'Wiki ID ou nome') with 100% coverage. The description adds no additional parameter semantics, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Obtém' = gets) and the resource ('detalhes de uma wiki específica' = details of a specific wiki). It distinguishes from sibling tools like azure_get_wiki_page (which fetches a page) and azure_list_wikis (which lists wikis).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or scenarios where another sibling tool would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the obvious side effect (creation) and does not mention anything about permissions, validation rules, overwrite behavior, or response format. This is minimal and insufficient for an agent to anticipate side effects beyond the basic creation action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence in Portuguese ('Cria uma nova iteration/sprint') that conveys the essential purpose without any wasted words. It is appropriately concise for a straightforward create operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no annotations, and no output schema, the description is quite sparse. However, the schema descriptions cover parameter semantics adequately, so the description is minimally acceptable for a simple create operation. It lacks additional context about what happens on success, error conditions, or relationship to other resources, but for a basic CRUD tool this is on the lower end of adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all five parameters (name, path, team, startDate, finishDate) individually described. The description itself adds no parameter information, but the schema already provides adequate semantics. Baseline 3 applies because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Cria uma nova iteration/sprint' clearly states the action (create) and the resource (iteration/sprint). This directly differentiates it from sibling tools like azure_list_iterations, azure_delete_iteration, and azure_get_current_iteration, which perform different operations on the same resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. There are no prerequisites, exclusions, or references to alternative tools for similar actions. The only implied usage is from the name 'create', but the description adds no contextual information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states that a team is created, but omits permissions, side effects, response format, or duplicate-handling behavior. For a mutating operation, this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler or redundant information. Every word contributes to conveying the action and resource, making it appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two parameters and a complete schema, but no output schema or annotations exist. The description provides only minimal context—creating a team—without explaining return values, prerequisites, or post-creation behavior, leaving some gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the schema already documenting 'name' and 'description' fields. The description adds no additional parameter-level meaning, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Cria' - creates) with a clear resource ('team') and scope ('projeto'), making the tool's function immediately obvious. It also distinguishes from sibling tools like azure_list_teams and azure_get_team by indicating a create operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description merely restates the creation action without mentioning prerequisites, exclusions, or 'use when' context, leaving the agent without comparative usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It only says 'Obtém detalhes' without specifying whether it returns all fields by default, the effects of the optional 'fields' parameter, potential errors, or authentication requirements. This is a generic statement that adds no behavioral context beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that states the tool's purpose without any filler or unnecessary details. It is well-structured and front-loaded, earning its place in the minimal space it occupies.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get-by-ID tool with two parameters and no output schema, this description is minimally adequate. It clearly indicates the core function but lacks details on return format or default field behavior. The schema covers the parameter semantics, and the sibling context helps clarify its role, but the description alone would leave a user wanting more context about expected outputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides descriptions for both parameters ('id' and 'fields') with 100% coverage. The description adds no additional meaning beyond what the schema already specifies. Baseline of 3 is appropriate as the schema does the heavy lifting for parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Obtém detalhes de um work item específico' clearly states the tool's verb (obtém) and resource (work item específico). It distinguishes itself from sibling tools like azure_create_work_item, azure_update_work_item, and azure_delete_work_item, and from azure_query_work_items which searches multiple items. The singular 'specific' implies fetching by ID, reinforced by the required 'id' parameter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it does not mention that this tool is for fetching a single work item by ID, while azure_query_work_items should be used for searching or listing. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. 'Lista' implies a read-only operation, but the description does not explicitly state that it has no side effects, nor does it mention pagination, ordering, or what fields are returned. It adds no behavioral context beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence: 'Lista todas as iterations (sprints) do time'. It contains no redundant information, is front-loaded with the verb and resource, and earns every word.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one optional parameter, but the description does not explain what the returned list contains (e.g., iteration names, dates, status) or mention the default team behavior (though the schema hint covers it). It is adequate but leaves gaps in return structure and edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for its one parameter 'team', which is already described as optional with a default team. The tool description repeats 'do time' but does not add any new meaning about the parameter beyond what the schema provides, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly uses the verb 'Lista' (Lists) with a specific resource 'iterations (sprints)' and scopes it to 'do time' (of the team). This distinguishes it from sibling tools like azure_get_current_iteration, azure_create_iteration, and azure_delete_iteration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention scenarios such as retrieving a single iteration (use azure_get_current_iteration) or creating/updating iterations, leaving the agent to infer usage solely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. It only states the update operation without explaining side effects, whether content is fully replaced, permission requirements, or any destructive aspects. This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wordiness. It conveys the core purpose while adding the key distinction 'existente'. It is appropriately sized, though it sacrifices behavioral detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple update tool with no annotations and no output schema, the description is insufficiently complete. It leaves unanswered questions about behavior, return values, and validation, which are expected for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear descriptions for all three parameters (path, content, wikiIdentifier). The tool description adds no additional parameter semantics, but the baseline is 3 given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Atualiza uma página existente na wiki' clearly conveys that this tool updates an existing wiki page, with the word 'existente' explicitly distinguishing it from the sibling create tool. It is specific in verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the verb 'Atualiza' and the resource 'página existente', but no explicit guidance is given on when to use this tool versus alternatives like create_wiki_page. There is no mention of prerequisites or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses only the act of creation but omits important behavioral context such as permissions required, default state auto-assignment, permanence of the creation, or response format. The schema includes a note about omitting 'state' on create, but this is not surfaced in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence in Portuguese that states the action and resource with the supported types. Every word is necessary, and there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 12-parameter creation tool with no annotations and no output schema, this description is under-specified. It fails to mention key operational context such as required type and title, default state behavior, or what the tool returns. The schema partially fills gaps, but the description should have at least referenced the most important behavioral constraints like 'omit state on create'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no parameter-level meaning beyond the schema; it merely lists the work item types, which are already defined in the enum. Since the schema fully documents all 12 parameters, the description provides no additional semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Cria' (creates) with a clear resource: 'um novo work item' in Azure DevOps, and lists the supported types (Task, Bug, User Story, etc.), which distinguishes it from sibling tools like update, delete, and query work item.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating 'Cria um novo work item' but does not explicitly state when to use versus alternatives, nor does it provide exclusions or mention azure_update_work_item for modifications. The intent is clear but not explicitly differentiated from other operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for disclosing behavior. It states 'Obter' (get), implying a read-only operation, but it does not explicitly mention side effects, authentication requirements, return format, or other behavioral traits. The description adds minimal value beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly communicates the tool's purpose without any fluff. Every word contributes meaning, making it appropriately sized for a simple get operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having only one parameter and no output schema, the description does not explain what the board configuration contains or what the tool returns. It also lacks guidance on when to use it over sibling tools. Given the absence of annotations and output schema, the description is incomplete for an agent to fully understand the tool's expected behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with boardId described as 'ID do board'. The description repeats this by saying 'por ID' (by ID), adding no extra meaning. Per the baseline for high schema coverage, this scores 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Obter' (get), the resource 'configuração de board' (board configuration), and the scope 'por ID' (by ID). It distinguishes itself from siblings like azure_list_boards and azure_update_board by specifying a single board's configuration retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a specific board ID is known, but it provides no explicit context on when to use this tool versus alternatives like azure_list_boards or azure_update_board. There is no mention of exclusions or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action without mentioning return format, error behavior, or confirming it is read-only, leaving significant behavioral details unstated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single clear sentence with no redundant words, front-loaded and appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and no output schema. While the description suffices for basic understanding, it lacks details on the shape of returned details or failure modes, making it adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter teamId described as 'ID ou nome do team'. The description adds no additional meaning beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves details for a specific team, using the verb 'obtém' (gets) and resource 'team específico'. It distinguishes from siblings like azure_list_teams and azure_create_team.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for fetching a single team's details but does not explicitly contrast with alternatives like azure_list_teams. No exclusions or prerequisites are mentioned, so usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It merely restates the operation implied by the tool name ('list boards') and adds minimal scope ('of the project'). It does not disclose behavioral traits such as pagination, authorization needs, or whether the operation is read-only, though 'list' implies read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that states the essential purpose without any fluff. It is appropriately sized for a simple, parameterless list operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is low-complexity with no parameters and no output schema, so the description is minimally adequate. However, it does not mention what is returned (e.g., board objects) or any limitations, and it could differentiate from sibling tools that might overlap in purpose. Given the minimal requirements, a score of 3 reflects the missing but not critical context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty, so the description does not need to explain parameter semantics. Per the baseline rule, a zero-parameter tool receives a score of 4 unless the description adds confusion, which it does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and the resource (boards) scoped to the project. This distinguishes it from sibling tools like azure_get_board_config, which retrieves a specific board's configuration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There is no mention of contexts where this is preferred, nor any exclusions or prerequisites. Users must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It simply states the action without disclosing any behavioral details such as response format, pagination, authentication requirements, or whether archived teams are included. For a read operation, this is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is front-loaded and efficient, earning a top score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (no params, no output schema), the description is minimally viable but lacks contextual depth. It does not clarify the return value or any edge cases, leaving the agent to infer standard list behavior. There is a clear gap in behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description appropriately does not need to explain parameter details. No additional meaning required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Lista todos os teams do projeto' clearly states the verb (list) and resource (all teams of the project). It distinguishes from siblings like azure_get_team (single team) and azure_create_team (create).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention that azure_get_team should be used for a specific team, nor any exclusions or prerequisites. The usage context is entirely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only says 'lists all Git repositories' and doesn't disclose return format, pagination, authentication requirements, or side effects. With no annotations, the description fails to provide meaningful behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly states the tool's purpose. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no params, no output schema), the description covers the core function adequately. However, it could benefit from mentioning that it returns a list of repository objects or referencing sibling get_repository for details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema confirms this. With no parameters to document, the description doesn't need to add parameter details, earning the baseline score of 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all Git repositories in the project, using a specific verb and resource. It distinguishes itself from sibling tools like azure_get_repository which targets a single repository.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as azure_get_repository. There is no mention of use cases, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It states the basic read behavior but does not disclose what happens if no active iteration exists, how 'current' is determined, how work items are represented, or any error conditions. This is a significant gap for a tool with no structured metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence in Portuguese that packs the essential information without any filler words. It is efficiently front-loaded and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple with no parameters, the lack of an output schema means the description should provide more insight into output structure. It mentions 'with work items' but does not specify the iteration fields or work item format, nor does it address edge cases like missing active iteration. Overall adequate but with gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema is fully covered. The description appropriately does not attempt to document parameters; the baseline for 0-param tools is 4, and the description adds no unnecessary param talk.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Obtém' (gets) and clearly identifies the resource as 'a iteration/sprint atual ativa' (current active iteration) with the differentiator 'com work items'. This distinguishes it from sibling tools like azure_list_iterations, which lists all iterations, and azure_get_iteration_capacity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving the current active sprint but does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or alternative tools. It's implied rather than explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of safety disclosure. The verb 'get' implies a read-only operation, but the description does not disclose response format, error handling, or any access requirements. For a simple read tool, this is minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly conveys the tool's purpose without any redundant or filler content. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a simple getter with one parametrized input, but the lack of an output schema and any mention of what 'details' includes leaves the agent uncertain about the response shape. It does the job for basic selection but lacks completeness for fully informed invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the single parameter with 100% coverage, describing it as 'ID ou nome do repositório Git'. The tool description adds no extra semantics beyond the word 'specific', so it meets the baseline but does not enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: retrieving details for a specific Git repository. The verb 'obtém' (gets) and the resource 'repositório Git específico' make it distinct from sibling tools like azure_list_repositories, which lists all repositories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context by specifying that the tool targets a specific repository, implying it should be used when the agent has a repository ID or name and needs details. However, it does not explicitly mention when to avoid using it or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. The verb 'Consulta' indicates a read-only query, and the 'use before' guidance provides behavioral context. However, it does not explicitly state that no modifications occur, nor does it describe the response format or any potential errors. Given the simplicity of the operation, this is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, with the primary purpose stated first and usage guidance second. No filler or redundant information; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter query tool with no output schema, the description covers the main points: what it does and when to use it. It does not mention the return format, but given the tool's simplicity and the clear naming, this is a minor gap. Overall, it is complete enough for an agent to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a full description and an enum for the single 'type' parameter, so the description adds no additional semantic value. The description does not elaborate on the parameter beyond what the schema states, so it earns the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Consulta' (queries) and names the resource 'estados válidos para um tipo de work item' (valid states for a work item type). This clearly distinguishes it from sibling create/update/delete tools. The scope 'no projeto' (in the project) adds context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to use the tool 'ANTES de criar ou atualizar work items' (BEFORE creating or updating work items) with a specific state. This gives a clear when-to-use directive. However, it does not mention when not to use it or explicitly name alternative tools, though the sibling context implies the create/update tools are the ones it precedes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Lista' indicates a read-only listing operation, but it does not disclose return format, pagination, or any authentication/permission requirements. For a simple list tool, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence that is front-loaded with the verb and object. It contains no wasted words and is easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with no output schema, the description is mostly complete. It clearly states what is listed, though it could mention that it returns a list of wikis or clarify 'project' context. Given the simplicity, this is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and an empty input schema, so schema coverage is 100%. There are no parameter details to clarify, and the description adds the useful context of project scoping. A baseline of 4 is appropriate for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Lista' (list), the resource 'wikis', and the scope 'do projeto' (of the project). This distinguishes it from sibling tools like azure_get_wiki (single wiki) and azure_list_wiki_pages (wiki pages).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied: use this tool when you need all wikis for a project. However, it does not explicitly mention alternatives or exclusions, such as using azure_get_wiki for a single wiki or azure_list_wiki_pages for pages within a wiki.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![mcp-azure-devops MCP server](https://glama.ai/mcp/servers/OnoSendae/mcp-azure-devops/badges/card.svg)](https://glama.ai/mcp/servers/OnoSendae/mcp-azure-devops)

Score Badge

Copy to your README.md:

[![mcp-azure-devops MCP server](https://glama.ai/mcp/servers/OnoSendae/mcp-azure-devops/badges/score.svg)](https://glama.ai/mcp/servers/OnoSendae/mcp-azure-devops)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/OnoSendae/mcp-azure-devops'

If you have feedback or need assistance with the MCP directory API, please join our Discord server