SwaggerMcp

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: fetching documentation, listing endpoints, getting endpoint details, executing requests, and validating responses. The descriptions make it easy to differentiate between discovery, execution, and validation phases.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern (e.g., fetch_swagger_info, list_endpoints, execute_api_request). The naming is predictable and follows the same convention throughout the set.
Tool Count5/5
Five tools is well-scoped for a Swagger/OpenAPI documentation server, covering the essential workflow from discovery to execution and validation. Each tool earns its place without feeling thin or bloated.
Completeness5/5
The tool set provides complete coverage for the domain: it supports fetching documentation, discovering endpoints, getting details, executing requests, and validating responses. There are no obvious gaps in the API interaction lifecycle.
Average 2.9/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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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?
With no annotations provided, the description carries full burden but only states the basic action without disclosing behavioral traits. It doesn't mention authentication needs, rate limits, error handling, or what the response looks like (especially since there's no output schema), which are critical for a general API tool.
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, efficient sentence with zero waste—it directly states the tool's purpose without fluff. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
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 the complexity of a general API execution tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error cases, or how to interpret results, leaving significant gaps for the agent to navigate.
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 fully documents all 5 parameters. The description adds no additional meaning beyond what's in the schema, such as examples or constraints, but the baseline is 3 since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Execute an API request to a specific endpoint' states a clear verb ('Execute') and resource ('API request'), but it's vague about scope and doesn't distinguish from siblings like 'fetch_swagger_info' or 'validate_api_response'. It lacks specificity about what type of API or what makes this tool unique.
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 like 'list_endpoints' or 'get_endpoint_details'. The description implies general API execution but doesn't specify contexts, prerequisites, or exclusions, leaving the agent to guess based on tool names 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 states the tool fetches documentation but doesn't disclose behavioral traits such as whether it requires authentication, how it handles errors, if it caches results, or what format the output is in. This leaves significant gaps for an agent to understand how to use it effectively.
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, clear sentence that efficiently conveys the core purpose. It's appropriately sized and front-loaded with the main action, though it could be slightly more structured by separating purpose from behavior.
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 the tool's complexity (fetching external documentation) and lack of annotations or output schema, the description is incomplete. It doesn't explain what the tool returns, how to interpret the results, or any prerequisites like network access, making it inadequate for an agent to use confidently.
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 the 'url' parameter fully. The description adds no additional meaning beyond what the schema provides, such as examples of common Swagger paths or clarification on the fallback behavior. Baseline 3 is appropriate when the schema does the heavy lifting.
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's purpose with a specific verb ('Fetch') and resource ('Swagger/OpenAPI documentation'), and explains what it does ('to discover available API endpoints'). It doesn't explicitly differentiate from siblings like 'list_endpoints' or 'get_endpoint_details', but the focus on documentation discovery is reasonably distinct.
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. With siblings like 'list_endpoints' and 'get_endpoint_details' that might overlap in functionality, there's no indication of when this tool is preferred or what its specific use case is compared to 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 carries the full burden of behavioral disclosure. It states the tool 'gets' information, implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns structured data (e.g., JSON), or handles errors. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves beyond basic functionality.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action ('Get detailed information'), making it easy to parse. Every part of the sentence earns its place by specifying the resource ('API endpoint') and scope ('specific'), achieving optimal conciseness.
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 the tool's moderate complexity (2 required parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain what 'detailed information' includes (e.g., response formats, error codes, or usage examples), which is critical for an API tool. Without annotations or output schema, the agent lacks context on return values and operational constraints, making this inadequate for effective use.
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% description coverage, with clear documentation for both 'path' and 'method' parameters. The description adds no additional semantic context beyond what the schema provides (e.g., it doesn't explain how the path and method combine to identify an endpoint or give examples beyond the schema's '/users/{id}'). Baseline 3 is appropriate since the schema does the heavy lifting.
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's purpose with a specific verb ('Get') and resource ('detailed information about a specific API endpoint'). It distinguishes from siblings like 'list_endpoints' (which likely lists multiple) and 'execute_api_request' (which performs the request rather than getting metadata). However, it doesn't explicitly mention what 'detailed information' includes (e.g., parameters, schemas, examples), which prevents a perfect score.
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 doesn't mention when to choose this over 'fetch_swagger_info' (which might provide broader API documentation) or 'validate_api_response' (which might check responses). There's no context about prerequisites, such as needing an endpoint path and method from 'list_endpoints' first, leaving the agent to guess usage 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. It mentions that endpoints are listed 'after fetching Swagger documentation', which adds some context about dependencies, but it doesn't disclose behavioral traits like whether this is a read-only operation, what the output format is, or if there are rate limits. The description is minimal and lacks essential operational details.
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 that states the purpose clearly without unnecessary words. It's appropriately sized for a simple tool, though it could be slightly more front-loaded by emphasizing the core action first.
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 the tool's simplicity (0 parameters, no output schema), the description is incomplete. It lacks details on what the output looks like (e.g., list format, fields), how it relates to siblings, and behavioral aspects like safety or dependencies. Without annotations or output schema, the description should provide more context to be fully helpful.
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 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The description doesn't add parameter semantics, but this is acceptable given the lack of parameters, warranting a baseline score of 4 for adequate handling.
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 action ('List all available API endpoints') and the resource ('API endpoints'), which is specific and unambiguous. However, it doesn't explicitly distinguish this tool from its sibling 'fetch_swagger_info' or 'get_endpoint_details', which likely have related but different purposes.
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 implies usage by mentioning 'after fetching Swagger documentation', but it doesn't provide explicit guidance on when to use this tool versus alternatives like 'fetch_swagger_info' or 'get_endpoint_details'. No exclusions or prerequisites are stated, leaving the agent to infer context.
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 states the tool validates responses against Swagger schemas, implying a read-only, non-destructive operation, but doesn't describe what happens on validation failure (e.g., error messages, partial validation), performance characteristics, or any authentication needs. For a tool with no annotations, this leaves significant behavioral gaps.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick understanding.
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's moderate complexity (4 required parameters, nested objects, no output schema), the description is minimally adequate. It explains what the tool does but lacks details on validation outcomes, error handling, or integration with sibling tools. Without annotations or an output schema, more context on behavior and results would improve completeness, but it meets a basic threshold.
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 description coverage is 100%, with all parameters documented in the input schema (path, method, statusCode, responseBody). The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to heavily.
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's purpose: 'Validate an API response against the schema from Swagger documentation.' It specifies the verb ('validate') and resource ('API response'), but doesn't explicitly differentiate from sibling tools like 'execute_api_request' or 'fetch_swagger_info' beyond the validation focus. This makes it clear but not fully sibling-distinctive.
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 doesn't mention prerequisites (e.g., needing Swagger documentation loaded), exclusions, or how it relates to siblings like 'execute_api_request' (which might produce responses to validate) or 'fetch_swagger_info' (which might provide schemas). Usage is implied from the purpose but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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