MamuteCloud
Server Details
MamuteCloud account data via OAuth login: storage, transcription, translation, analytics.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 5 tools
Each tool has a distinct role in a clear pipeline: list-specs selects a spec, list-endpoints and search-endpoints discover operations, get-endpoint fetches details, and execute-request performs the call. The only mild overlap is between list-endpoints (browse all paths) and search-endpoints (keyword discovery), but the descriptions make the browse-vs-search distinction reasonably clear.
All five tools follow a uniform kebab-case verb_noun pattern: execute-request, get-endpoint, list-endpoints, list-specs, search-endpoints. Verbs are meaningful and consistently applied (list for enumeration, get for single-item retrieval, search for discovery, execute for action).
Five tools is a tight, well-scoped surface for an OpenAPI exploration-plus-execution server. Each tool earns its place and there is no redundancy or filler.
The surface covers the full workflow from spec listing through endpoint discovery, detail retrieval, and request execution. Minor gaps remain, such as no tool for adding/loading a spec by URL or configuring authentication, but core lifecycle coverage is solid.
Available Tools
5 toolsexecute-requestExecute API RequestADestructiveInspect
Executes an API request with a given HAR request object.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | Title of the OpenAPI spec. Use tool 'list-specs' or 'search-endpoints' to see available specs. | |
| harRequest | Yes | HAR request object |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructive behavior (destructiveHint: true) and non-read-only status (readOnlyHint: false). The description adds no extra behavioral context, such as side effects on external systems, authentication requirements, or rate limits. It does not contradict annotations, but also does not enrich them.
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 efficiently conveys the core purpose. It contains no fluff or redundant information, and every word contributes to explaining what the tool does.
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 tool executes arbitrary API requests, but the description does not mention what the response looks like, error behavior, or potential side effects beyond what annotations hint. Since there is no output schema, the description should at least indicate that a response is returned. The schema covers parameters, but the overall context for an agent is incomplete.
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 100%, with detailed descriptions for parameters including the HAR request object's subfields (method, url, postData variants, etc.). The tool description itself adds no parameter-specific meaning, but the schema already provides strong semantics, so a baseline score of 3 is appropriate.
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: 'Executes an API request with a given HAR request object.' This uses a specific verb ('executes') and resource ('API request') and distinguishes it from sibling tools that focus on listing/searching endpoints rather than making actual calls.
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 for executing API requests, but it does not explicitly state when to use it versus alternatives. The only related guidance is in the schema's title parameter, which mentions using 'list-specs' or 'search-endpoints' to see available specs—this is more about parameter resolution than tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-endpointGet Endpoint DetailsBRead-onlyInspect
Gets detailed information about a specific API endpoint, including security schemes and servers
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | The API endpoint path (e.g. /api/v1/users). | |
| title | Yes | Title of the OpenAPI spec. Use tool 'list-specs' or 'search-endpoints' to see available specs. | |
| method | Yes | The HTTP method (e.g. GET, POST, PUT, DELETE). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that security schemes and servers are returned, which gives some output context, but it does not describe response format, errors, or prerequisites beyond the schema.
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?
A single sentence with no filler, front-loaded with the core action. Every word contributes to the purpose, and the structure is optimal for quick parsing.
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 simple read-only lookup with fully documented parameters and safety annotations, the description is mostly adequate. The return content is partially described (security schemes and servers), but 'detailed information' remains vague, and without an output schema more specifics would help.
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 100% and each parameter (path, title, method) is well documented with examples and cross-tool hints. The description adds no parameter-specific meaning; it only implies the endpoint is identified by these fields, 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb and resource: 'Gets detailed information about a specific API endpoint' and names included content (security schemes, servers). It distinguishes from siblings implicitly via 'specific' (vs list/search), but does not explicitly name any alternative.
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 this tool versus alternatives. The description does not include conditions, exclusions, or mentions of sibling tools; the schema's title parameter suggests list-specs/search-endpoints but that lies outside the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list-endpointsList API EndpointsARead-onlyInspect
Lists all API paths and their HTTP methods with summaries, organized by path. Results can be passed directly into 'get-endpoint'.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | Title of the OpenAPI spec. Use tool 'list-specs' or 'search-endpoints' to see available specs. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the organizational detail (grouped by path) and the direct compatibility with 'get-endpoint', which is useful. However, it doesn't disclose details like pagination, response size, or whether all specs' endpoints are listed or just the current spec, which would be valuable context.
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?
Two sentences with no fluff. The core function is front-loaded, and the second sentence adds a valuable workflow hint. Every word earns its place.
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 listing tool with a single well-documented parameter and no output schema, the description is nearly complete. It tells the agent what it returns (paths, methods, summaries), how it's organized, and how to use the results. The only minor gap is not specifying whether the list covers all specs or just one, but the parameter implies a specific spec.
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 100%, so the schema already documents the 'title' parameter. The description doesn't add much beyond the schema, but it does reinforce that the title refers to an OpenAPI spec and points to sibling tools for discovering available specs. This is baseline 3 territory since the schema carries the load.
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 all API paths and their HTTP methods with summaries, organized by path. It distinguishes itself from siblings by noting results can be passed directly into 'get-endpoint', which is a specific and useful differentiation.
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 when to use this tool: to get an overview of all endpoints, and it hints at the workflow by saying results can be passed to 'get-endpoint'. It doesn't explicitly state when not to use it or name alternatives like 'search-endpoints' for filtering, but the context is clear enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list-specsList OpenAPI SpecsARead-onlyInspect
Lists all available OpenAPI specs. Use the title to select a spec.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds no further behavioral context (e.g., pagination, output format, or size limits). Since the annotations carry the burden, a 3 is appropriate—the description doesn't contradict or extend beyond what annotations provide.
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, efficient sentence that immediately states the action and provides a practical hint. There is no fluff or redundant information. It earns a top score for conciseness.
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 tool's simplicity (no params, no output schema) and that annotations cover safety, the description is fairly complete. It tells the agent what the tool returns (available specs) and how to use that result (select by title). It doesn't specify the exact output structure, but for a listing tool, this is likely sufficient for an agent to proceed. A 4 is reasonable.
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 tool has zero parameters, so the schema trivially covers all parameters (100% coverage). The baseline for 0 params is 4. The description's note about using the title to select a spec applies to the output, not parameters, so it doesn't add param-specific meaning, but no param semantics are needed. A 4 is fair.
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 clear verb ('Lists') and resource ('all available OpenAPI specs'), and the title reinforces it. It distinguishes itself from siblings like list-endpoints and search-endpoints by specifying 'specs' rather than endpoints, though it doesn't explicitly contrast them. Still, the purpose is 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?
The description gives no guidance on when to use this tool versus alternatives. It only hints at a follow-up action ('Use the title to select a spec') but does not mention any other tools or exclusions. An agent would have to infer usage from the name and siblings, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search-endpointsSearch API EndpointsARead-onlyInspect
Performs a deep search through paths, operations, and parameters to discover relevant API endpoints. Use this tool to find specific API capabilities, required parameters, or data models based on search keywords. Results can be passed directly into 'get-endpoint'.
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | Yes | Search pattern (case-insensitive) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds useful behavioral context by stating that search results can be passed directly into 'get-endpoint', implying the output is compatible with that tool's input. It also mentions 'deep search' but doesn't detail pagination or rate limits; given annotation coverage, the added workflow info justifies a 4.
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 two sentences, front-loaded with the core purpose, and every clause contributes value. No filler or repetition.
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 single-parameter search tool with annotations covering safety and no output schema, the description is quite complete. It states what it does, when to use it, and how results feed into 'get-endpoint'. It doesn't describe the return format in detail, but the workflow hint mitigates that. Missing explicit mention of alternatives or edge cases, but adequate for typical agent use.
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 coverage is 100%, so the parameter 'pattern' is documented. The description adds meaning by explaining that the pattern searches through 'paths, operations, and parameters', which goes beyond the schema's generic 'Search pattern (case-insensitive)'. This clarifies what the pattern can match, adding value.
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 purpose: performing a deep search through paths, operations, and parameters to discover relevant API endpoints. It uses a specific verb ('search') and resource ('API endpoints'), and clarifies the scope of the search. However, it does not explicitly differentiate from sibling 'list-endpoints' (which likely lists all endpoints), leaving some ambiguity about when to choose this over listing.
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 provides clear usage context: 'Use this tool to find specific API capabilities, required parameters, or data models based on search keywords.' It also notes that results can be passed to 'get-endpoint', implying a workflow. However, it does not explicitly state when not to use it or mention alternatives like 'list-endpoints' or 'execute-request', so exclusions are absent.
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.
1 tool update
- Removed
get-server-variables
6 tool updates
- First observed
execute-request - First observed
get-endpoint - First observed
get-server-variables - First observed
list-endpoints - First observed
list-specs - First observed
search-endpoints
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