Swagger MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap. 'api_list_endpoints' lists available endpoints, 'api_get_endpoint_info' provides details for a specific endpoint, and 'api_call' performs actual API calls. The descriptions clearly differentiate their functions, making misselection unlikely.
Naming Consistency5/5All tools follow a consistent 'api_verb_noun' naming pattern (api_list_endpoints, api_get_endpoint_info, api_call). The structure is uniform throughout, using snake_case and starting with 'api_' as a prefix, which enhances predictability and readability.
Tool Count3/5With only 3 tools, the set feels thin for a server named 'Swagger MCP Server', which implies broader API documentation or management capabilities. While the tools cover basic operations (list, get info, call), the scope suggests more tools might be expected for comprehensive API interaction, such as schema validation or endpoint testing.
Completeness4/5The tools provide a logical workflow: list endpoints, get endpoint details, and make API calls, covering core operations for interacting with an API. However, there are minor gaps, such as no tools for managing API schemas, authentication, or error handling, which could limit advanced use cases but are workable for basic needs.
Average 2.8/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool supports all HTTP methods and paths, implying it can perform various operations (e.g., GET, POST, DELETE), but does not disclose critical behavioral traits such as authentication requirements, rate limits, error handling, or whether it's safe or destructive. For a general-purpose API tool with no annotations, this is a significant gap in 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?
The description is concise with two sentences that directly state the tool's general function and capabilities. It is front-loaded and wastes no words, though it could be slightly more informative without losing efficiency. The structure is clear but minimal, earning a high score for brevity and directness.
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?
Given the tool's complexity (6 parameters, no output schema, no annotations), the description is incomplete. It lacks details on behavioral aspects like authentication, error handling, or response formats, which are crucial for a general API tool. Without annotations or output schema, the description should provide more context to guide the agent effectively, but it falls short, leaving significant gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with detailed descriptions for all parameters in the input schema (e.g., 'HTTP方法' for method, 'API路径' for path). The description adds no additional meaning beyond the schema, as it only mentions supporting all HTTP methods and paths without explaining parameter interactions or usage. With high schema coverage, the baseline score of 3 is appropriate, as the schema adequately documents parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool '调用示例API API的通用工具' (calls example API general tool) and '支持所有HTTP方法和路径' (supports all HTTP methods and paths), which provides a vague purpose. It mentions the general function but lacks specificity about what resources it operates on or how it differs from siblings like 'api_get_endpoint_info' and 'api_list_endpoints'. The description is not tautological but remains broad without clear differentiation.
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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, such as when to choose this over sibling tools like 'api_get_endpoint_info' for endpoint details or 'api_list_endpoints' for listing. Without explicit or implied usage instructions, the agent lacks direction on appropriate tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves detailed information, implying a read-only operation, but doesn't specify what '详细信息' (detailed information) includes—such as response formats, error handling, rate limits, or authentication needs. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 a single, efficient sentence: '获取示例API API特定端点的详细信息'. It's front-loaded with the core action and resource, with zero wasted words. Every part of the sentence contributes directly to clarifying the tool's purpose, making it highly concise and well-structured.
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?
Given the complexity (a tool with 2 required parameters, no annotations, and no output schema), the description is incomplete. It doesn't explain what '详细信息' entails—such as the structure or type of information returned—leaving the agent uncertain about the tool's output. For a tool that retrieves endpoint details, more context on the expected result is needed to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with parameters 'method' (HTTP method with enum values) and 'path' (API path) clearly documented. The description adds no additional meaning beyond what the schema provides—it doesn't explain parameter interactions, examples, or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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's purpose: '获取示例API API特定端点的详细信息' (Get detailed information about a specific endpoint of the example API). It specifies the verb ('获取' - get) and resource ('API特定端点的详细信息' - detailed information about a specific API endpoint), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'api_list_endpoints' (which likely lists endpoints rather than getting details for one).
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'api_call' (which might invoke an endpoint) or 'api_list_endpoints' (which might list endpoints), nor does it specify prerequisites, contexts, or exclusions for usage. The agent must infer usage from the tool name and description 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 of behavioral disclosure. It states the tool lists endpoints but doesn't describe behavioral traits like whether it's a read-only operation, if it requires authentication, rate limits, pagination, or the format of the returned data. For a tool with no annotations, this leaves significant gaps in understanding how it behaves.
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 a single, efficient sentence in Chinese: '列出示例API API的所有可用端点'. It is front-loaded with the core action and resource, with no unnecessary words or redundancy. Every part of the sentence contributes directly to the tool's purpose, making it highly concise and well-structured.
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?
Given the lack of annotations and output schema, the description is incomplete for effective tool use. It doesn't explain what the output looks like (e.g., list format, data structure), behavioral aspects like safety or performance, or how it relates to sibling tools. For a tool with no structured metadata, the description should provide more context to compensate, but it falls short.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 parameters ('filter' and 'method'), including an enum for 'method'. The description adds no additional meaning beyond what the schema provides, such as examples or usage tips. With high schema coverage, the baseline score of 3 is appropriate, as the schema adequately handles parameter semantics.
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's purpose: '列出示例API API的所有可用端点' (List all available endpoints of the example API API). It specifies the verb '列出' (list) and resource '端点' (endpoints), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'api_get_endpoint_info', which might provide detailed information about a specific endpoint.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools such as 'api_call' or 'api_get_endpoint_info', nor does it specify any prerequisites, exclusions, or contextual cues for usage. The agent must infer usage based on the tool name and description alone.
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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