One AI Guide
Server Details
Read-only approved AI tools, public stacks, guides, and evidence-aware comparisons.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
7 toolscompare_toolsARead-onlyIdempotentInspect
Compare 2 to 5 distinct approved tools with evidence-backed objective facts.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | ||
| toolIds | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that comparisons are evidence-backed and objective, and that only approved tools can be compared, but it does not explain behavior such as error handling for invalid IDs or how locale affects results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It conveys the action, the resource, the count range, and the evidence-based nature of the output in minimal space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only comparison tool whose schema already documents the UUID list and locale enum, the description plus annotations cover most invocation needs. The main missing pieces are the output shape and the precise meaning of 'approved', but the tool is otherwise simple enough to be adequately specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate for the lack of parameter documentation. It adds 'distinct' and 'approved' semantics for toolIds but does not explain the locale parameter or elaborate on what 'approved tools' means, leaving a meaningful gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Compare'), a clear resource ('tools'), and an explicit constraint (2 to 5 distinct approved tools). It also signals the output nature ('evidence-backed objective facts'), which distinguishes it from sibling tools like get_tool or search_tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for comparing multiple tools, and the '2 to 5' constraint gives some usage context. However, it does not explicitly state when to prefer compare_tools over search_tools or get_tool, nor does it mention any exclusions or alternative conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_guideARead-onlyIdempotentInspect
Get a published guide by slug.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| locale | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only, idempotent, and non-destructive, so the description only needs to add context beyond that. It adds the 'published' scoping detail, but it does not disclose behavior for unpublished slugs, locale fallback, or error responses. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler or redundancy. It is appropriately sized for a simple retrieval tool and every word contributes to the meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema and annotations cover parameter constraints and safety, but there is no output schema and the description does not describe the returned guide structure, behavioral edge cases, or locale semantics. The definition is adequate for a basic getter but leaves meaningful gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the input schema. It clarifies that slug is the lookup identifier, but it completely omits the optional locale parameter, its meaning, and how it affects the returned guide. This is a significant gap for a two-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') with a clear resource ('published guide') and identifier ('slug'), making the tool's purpose immediately understandable. It is distinguishable from siblings such as list_guides, get_tool, and get_stack by resource type and retrieval semantics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when you have a specific guide slug, but it does not explicitly state when to use this versus alternatives like list_guides. No exclusions or alternative routing are provided, so the usage guidance remains inferred rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_stackBRead-onlyIdempotentInspect
Get a public approved stack.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| locale | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the 'public approved' scope, which is meaningful behavioral context about visibility/approval, but it does not disclose error behavior or locale effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler; every word contributes to the basic meaning. It is efficient, though it sacrifices detail that would improve usability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple read-only tool with rich annotations, but the description omits the optional locale's role, how stack IDs are discovered, and any return-format information given the absence of an output schema. It is minimally adequate but leaves notable gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it only references 'stack' without explaining that id is the stack UUID or what the locale parameter controls. The schema's type and enum provide structure but not semantic meaning, leaving locale unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Get'), resource ('stack'), and qualifier ('public approved'), making the core operation clear. It distinguishes from get_guide and get_tool by resource, though it does not explicitly differentiate itself from sibling list_stacks beyond singular versus plural phrasing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use get_stack versus alternatives like list_stacks or search_tools. The description does not mention prerequisites or discovery flows, such as obtaining a stack ID via list_stacks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_toolARead-onlyIdempotentInspect
Get one approved tool by UUID or canonical slug.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| locale | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, and non-destructive behavior, so the description only needs to add context beyond that. It adds useful behavioral constraints: the tool returns only one entity and only approved tools. It does not describe error responses, but the safety profile is already covered by annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short, front-loaded sentence with no filler or redundant phrasing. Every word contributes to specifying the operation, the resource, and the identifier semantics.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple two-parameter schema and strong annotations, the description is nearly complete for correct invocation. It explains the critical `id` parameter and implies the return is a single tool object, though the effect of the optional `locale` parameter is left implicit. No output schema exists, but the tool's name and 'get one tool' wording sufficiently convey the basic return shape.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does clarify that `id` accepts a UUID or canonical slug, which is meaningful beyond the raw string schema, but it says nothing about the `locale` parameter. The locale enum values make the intended purpose inferable, but the description still leaves that parameter's semantics unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get'), a clear resource ('tool'), and the unique qualifiers 'one approved tool' and 'by UUID or canonical slug'. This clearly distinguishes it from siblings like get_guide, get_stack, search_tools, and the list_* tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when you already have a UUID or canonical slug and need a single approved tool, but it never explicitly states when to prefer search_tools for discovery or compare_tools for comparison. No exclusion criteria or alternative routing is given, so usage guidance is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_guidesBRead-onlyIdempotentInspect
List published guides linked only to approved tools.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| locale | No | ||
| offset | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation read-only, idempotent, and non-destructive. The description adds the filtering behavior (only published guides linked to approved tools), which goes beyond annotations. It omits details like pagination and response shape, but for a safe read operation this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence that packs the verb, resource, and filter criteria with no wasted words. It achieves maximal information density for the purpose it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core resource and filtering rule, which is enough to understand what the tool lists. However, with no output schema and no parameter explanation, the agent is left without details on pagination, locale handling, or the returned structure. This is a moderate gap, not a fatal one.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description needed to compensate by explaining limit, locale, and offset. It doesn't mention any parameters. While the parameter names are reasonably self-explanatory and the schema provides ranges and enums, the description still leaves a gap for an agent unfamiliar with expected values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List'), a target resource ('guides'), and clear qualifiers ('published', 'linked only to approved tools') that make the tool's scope explicit and distinct from sibling tools like get_guide or list_stacks. The purpose is immediately unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool vs alternatives such as search_tools or list_stacks. No exclusions or alternative routes are mentioned, so the agent must infer the appropriate use case from the filter conditions alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_stacksARead-onlyIdempotentInspect
List approved public or template stacks whose tools are approved.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| locale | No | ||
| offset | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds that it filters for 'approved' stacks, providing additional behavioral context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no extraneous information. It is concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, and the description does not mention what fields the returned stacks contain or provide any details about the response format. This is a significant gap for a listing operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no descriptions for limit, locale, or offset (0% coverage). The description does not explain any of these parameters, leaving the agent to infer their meaning from common conventions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: listing stacks that are approved, public, or template. This is distinct from siblings like get_stack (retrieving a single stack) or search_tools (searching tools).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case (listing approved public/template stacks) but does not explicitly compare with alternatives or state when to use this versus search_tools or list_guides.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_toolsBRead-onlyIdempotentInspect
Search approved One AI Guide tools.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | ||
| limit | No | ||
| locale | No | ||
| offset | No | ||
| category | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description need not restate safety. It adds the 'approved' scope, but does not disclose result shape, pagination behavior, or empty-result semantics; with the safety profile covered, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler or repetition. It is appropriately sized for a simple search tool, even though other dimensions carry the burden of missing detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no parameter descriptions, the definition does not explain return format, how 'approved' is determined, or how the search, locale, and pagination parameters interact. The annotations cover safety, but the description is too thin for an agent to confidently predict search behavior and results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate for the five unnamed parameters. It does not describe q, limit, locale, offset, or category beyond what the schema types and names already imply, leaving their intended semantics mostly inferred.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Search approved One AI Guide tools.' It is clear this is a query/filter action over tools rather than retrieval (get_tool), comparison (compare_tools), or guides/stacks, although it does not explicitly call out sibling distinctions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Searching is implied as the use case, and the parameter set suggests querying with q, limit, offset, locale, and category, but there is no explicit when-to-use guidance or statement of alternatives. The description leaves the agent to infer that get_tool/compare_tools are for other purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
7 tool updates
- First observed
compare_tools - First observed
get_guide - First observed
get_stack - First observed
get_tool - First observed
list_guides - First observed
list_stacks - First observed
search_tools
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
Each tool targets a distinct resource and action: get/list for guides, stacks, and tools, plus a dedicated search and compare tool. There is no meaningful overlap between get_tool and search_tools because one is direct retrieval and the other is discovery.
All tool names follow a consistent verb_noun pattern using lowercase snake_case. get_*, list_*, search_*, and compare_* are predictable and easy to group by intent.
Seven tools is well-scoped for a knowledge/discovery server focused on tools, stacks, and guides. Each tool covers a clear need without redundancy or bloat.
The core read-only surface is well covered: guides and stacks have get/list, tools have get/search/compare. The main minor gap is the lack of a dedicated list_tools or search for guides/stacks, though agents can likely work around this with the existing tools.