Redmine MCP Server
Server Quality Checklist
Latest release: v0.3.0
- Disambiguation5/5
All tools have clearly distinct purposes: add_comment is for issue comments, create_issue for creation, download_attachment for downloading, get_issue for details, get_my_today for personalized summary, get_wiki for wiki content, list_enumerations for IDs, list_issues for listing, list_projects for projects, list_wiki_pages for wiki listing, and update_wiki for wiki modification. No two tools overlap in functionality.
Naming Consistency4/5Tool names follow a consistent snake_case verb_noun pattern (e.g., create_issue, list_projects). The only minor deviation is 'get_my_today' which uses a possessive 'my_today', but it remains readable and fits the pattern of other 'get_' tools.
Tool Count5/5With 11 tools covering issues, wiki, projects, attachments, and enumerations, the number is well-scoped. Each tool earns its place without redundancy, appropriate for a Redmine MCP server.
Completeness3/5Core operations for issues (create, read, add comment) and wiki (get, list, upsert) are present, but missing update and delete for issues, and delete for wiki. This leaves notable gaps in lifecycle coverage, though the surface handles common workflows.
Average 3.7/5 across 11 of 11 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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
This repository is licensed under MIT License.
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.jsonto 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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behavioral traits. It only says '조회' (retrieve), implying read-only, but does not state what happens if the page does not exist, whether permissions are needed, or if the content is returned as raw text or structured data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is short and front-loaded with the main action. The Args block is structured clearly. However, it could be more concise by omitting the redundant parameter listing that duplicates the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description should at least hint at what is returned (e.g., page content in markdown). It lacks this, making it incomplete for an agent to know what to expect. Error cases are also not covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It provides brief labels: '프로젝트 식별자' (project identifier) and '페이지 제목' (page title), which add minimal context over the schema's 'Project Id' and 'Page Name'. No formatting, sources, or examples are given, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states '위키 페이지 내용 조회' (Retrieve wiki page content), clearly indicating a read operation on a specific resource. While it distinguishes from sibling tools like 'list_wiki_pages' (list) and 'update_wiki' (update), it does not specify the exact scope of content returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. It does not mention prerequisites, such as needing a project_id from another source, or when to use 'list_wiki_pages' first to find a page_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 must disclose behavioral traits. It only states the basic action without mentioning read-only nature, pagination, error handling, or any side effects. The output schema exists but behavior like listing all pages versus paginated is not specified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short, with one sentence followed by an Args list. It is concise and avoids unnecessary words. However, it could be structured more efficiently by including the parameter description inline without the separate Args block.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool being simple with one parameter and having an output schema, the description lacks critical context such as usage guidelines, behavioral traits, and sufficient parameter semantics. An agent would need additional assumptions to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description should compensate. The description of 'project_id' as '프로젝트 식별자' merely repeats the schema's 'Project Id' in Korean, adding no further meaning about format, source, or constraints. It is almost a tautology.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states '프로젝트의 위키 페이지 목록' which clearly indicates listing wiki pages of a project. The verb 'list' and resource 'wiki pages' are specific. While it does not explicitly differentiate from siblings like 'get_wiki' or 'update_wiki', the action is distinct enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 such as 'get_wiki' or 'list_issues'. There are no prerequisites, context, or exclusion criteria mentioned. The description is purely factual without usage recommendations.
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 tool lists projects without mentioning pagination, authentication, rate limits, or any side effects. This is minimal and insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is concise and front-loaded, though it could be expanded slightly with behavioral details without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with no parameters and an output schema exists (not shown). The description covers the basic purpose and fields returned. It is adequately complete for a straightforward list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so schema description coverage is trivially 100%. The description adds no parameter information, but none is needed. Baseline score of 4 for no parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a list of Redmine projects with specific fields (identifier, name, description). It is a specific verb+resource combination, but does not differentiate from sibling tools that target other resources, which is acceptable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. However, the simple purpose of listing projects makes usage straightforward and 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?
No annotations exist, so description carries full burden. It only states the action without disclosing side effects, error conditions, or requirements like authentication. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is brief with a one-line summary followed by a structured Args list. Efficient and clear, though the summary could be more descriptive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter tool without output schema, the description covers parameter semantics but omits behavioral context like return values or common errors. Adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the tool description's Args list explains all three parameters: issue_id (issue number), note (content, Markdown possible), and status_id (optional status change, default keep). Adds significant meaning beyond bare schema types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool adds a comment to an issue with optional status change. Verb 'add' and resource 'comment' are specific, distinguishing it from siblings like create_issue or get_issue.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use vs alternatives, no context for when not to use or prerequisites. Only a raw parameter list.
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 provided. Description does not disclose error handling, authentication needs, rate limits, or what happens if issue doesn't exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences summarizing purpose and parameters. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers basic function and parameters but lacks output format details and edge case handling. Acceptable for simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description adds full explanation for both parameters beyond schema titles, including example for issue_id and default for include_comments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states tool retrieves issue details including body, comments, and attachments. It distinguishes from siblings like list_issues and add_comment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 (e.g., list_issues for summaries). Missing context about prerequisites or limitations.
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 only states the tool creates an issue. It does not disclose side effects, idempotency, authorization requirements, or whether duplicates are prevented. The mutation nature is implied but not elaborated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a one-line summary followed by a bullet list of parameters. Every sentence adds value, and the structure is front-loaded and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While parameter semantics are well-covered, the description omits return value details, error conditions, and behavioral context (e.g., consequence of duplicates). Given no output schema and no annotations, more completeness would help agent decisions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates fully by explaining each parameter's meaning, including formats (YYYY-MM-DD), markdown support, and references to list_enumerations for tracking and priority IDs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with '새 이슈 생성' (Create new issue), clearly stating the verb and resource. It distinguishes from sibling tools like get_issue or list_issues by focusing on creation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a parameter hint to use list_enumerations for tracker_id, but lacks explicit guidance on when to use this tool versus others, or any prerequisites beyond required parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given no annotations, the description discloses key behavioral traits: inline rendering for images, error for non-images, and suggestion to use content_url. It lacks details on authentication or side effects, but for a download tool, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively concise, with the key action in the first sentence. The usage guidance and parameter info are front-loaded. Slight redundancy in repeating '첨부파일' could be tightened, but overall well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core functionality and edge cases (image vs non-image) without an output schema. It lacks details on error messages or return format, but the tool's behavior is sufficiently explained for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal meaning beyond the input schema: it only restates the parameter as 'attachment file ID'. With 0% schema coverage, the description should compensate but does not provide additional context or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: downloading attachments and inline display for images. It distinguishes itself by specifying behavior for two types of attachments, which is not covered by sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (for image attachments) and what to do for non-images (use content_url directly). However, it does not explicitly contrast with sibling tools, though no sibling handles downloads.
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. It discloses parameter behaviors (defaults, allowed values) but lacks details on pagination, return format, or edge cases like empty results. It adequately explains input but not output behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a one-line purpose followed by a structured Args block with one line per parameter. No extraneous text, every sentence serves a purpose. Front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Input parameters are well explained, but the description lacks details about the output (e.g., what fields are returned, structure of issue objects). Given no output schema, this gap reduces completeness. Error handling or ordering behavior beyond sort is also missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by explaining all 7 parameters with context such as defaults, allowed values (e.g., status: 'open','closed','*'), and format (e.g., sort: 'updated_on:desc'). This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as '일감 목록 조회' (List issues), which is a specific verb+resource combination. It distinguishes itself from siblings like get_issue (single issue) and create_issue by focusing on listing multiple issues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains parameters for filtering but does not explicitly state when to use this tool versus alternatives like get_issue or list_projects. No usage guidance or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the behavioral burden. It transparently explains the tool returns two types of tasks (incomplete assigned tasks and recently updated tasks) without side effects, though it omits details like rate limits or data freshness guarantees.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear main sentence and bullet-pointed details. No unnecessary words; each sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description sufficiently explains the tool's purpose and output. It could detail the output format further, but overall it is complete for an agent to understand usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters (100% coverage), so the description adds value by describing the output structure (two sub-sections). This clarifies what the tool returns, going beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves today's tasks at once ('오늘 봐야 할 일감 한 번에 조회') and lists two specific sections: my_open_issues and recently_updated. This distinguishes it from sibling tools that focus on single issues or general lists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it is structured for morning alert scripts, implying usage for daily overviews. However, it does not explicitly state when not to use it or compare alternatives, leaving usage guidance implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description explains upsert behavior (create if not exists, update if exists). No annotations provided, but the description conveys key behavioral traits clearly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: two lines for purpose, then structured argument list. No wasted words, front-loaded with main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all 5 parameters meaningfully. Missing return information but no output schema exists. Adequate for typical usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
0% schema description coverage, but description adds meaningful explanations for each parameter, e.g., 'text: 본문 (Textile 또는 Markdown)' and 'parent_title: 상위 페이지 제목 (계층 구조)'. Adds value beyond schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'create/update wiki page (create if not exists, update if exists)' with specific verb and resource. Distinguishes from siblings like 'get_wiki' and '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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use vs alternatives, but the purpose is self-explanatory given siblings. Adequate but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
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 that the tool returns IDs for three enumeration categories. For a simple read-only listing tool, this is adequate; no destructive actions or side effects are implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using a single sentence and bullet points. Every word adds value, and the structure is clear and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and no output schema, the description provides all necessary context: what the tool returns and why it is used. It is complete for its complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so baseline is 4. The description adds meaning by listing the enumeration categories, which goes beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides ID lists needed for issue creation/filtering, specifying three types (trackers, statuses, priorities). This is distinct from sibling tools like list_issues or create_issue, which operate on actual issues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly tells when to use this tool (when needing IDs for issue creation/filtering), but does not explicitly exclude scenarios or mention alternatives. However, the context is clear enough for an agent.
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:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/junstellar/redmine-mcp-jun'
If you have feedback or need assistance with the MCP directory API, please join our Discord server