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saurav61091

mcp-openapi-runner

by saurav61091
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TypeScript
Hybrid

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.2

  • Disambiguation5/5

    The two tools have completely distinct purposes: list_endpoints is for discovery and metadata retrieval, while call_endpoint is for executing operations. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with clear, descriptive names (list_endpoints and call_endpoint). The naming convention is uniform and predictable throughout the set.

    Tool Count2/5

    With only 2 tools, this server feels thin for its purpose of interacting with an OpenAPI specification. While it covers basic discovery and execution, it lacks tools for more advanced operations like schema inspection, parameter validation, or response handling, making the scope appear underdeveloped.

    Completeness3/5

    The toolset provides a minimal viable surface for calling endpoints and listing them, but there are notable gaps. For example, it lacks tools for managing authentication, handling different HTTP methods explicitly, or validating requests against the OpenAPI schema, which could limit agent effectiveness in complex scenarios.

  • Average 4/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • 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.

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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 the full burden of behavioral disclosure. While it mentions the need to use 'list_endpoints' first for discovery, it doesn't describe what happens when the tool is invoked (e.g., HTTP method implications, error handling, authentication requirements, rate limits, or what the response looks like). For a tool that makes API calls, 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 perfectly concise - two sentences that each earn their place. The first sentence establishes the core purpose, and the second provides essential usage guidance. There's zero waste or redundancy.

    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?

    For a tool that makes API calls with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, how errors are handled, authentication requirements, or the implications of different HTTP methods. The usage guidance is helpful but doesn't compensate for the missing behavioral context needed for effective tool invocation.

    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 all three parameters thoroughly. The description adds minimal value beyond what the schema provides - it mentions 'operationId' and 'parameters' in the context of discovery but doesn't provide additional semantic context about how these parameters interact or when to use 'body' versus 'parameters'. 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 action ('Call an endpoint') and the target resource ('in the Swagger Petstore - OpenAPI 3.0'), providing a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from its sibling 'list_endpoints' beyond mentioning it should be used first for discovery, which is more of a usage guideline than a purpose distinction.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description explicitly states when to use this tool ('Use list_endpoints first to discover available operationIds and their required parameters'), providing clear guidance on prerequisites and the relationship with the sibling tool. This tells the agent exactly how to approach using this tool effectively.

    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?

    No annotations are provided, so the description carries the full burden. It discloses that this is a read-only discovery tool ('List all available endpoints'), which implies safe, non-destructive behavior. However, it lacks details on potential rate limits, authentication needs, or response format, leaving some behavioral aspects unspecified.

    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 front-loaded with the core purpose in the first sentence and follows with a concise usage guideline. Every sentence earns its place by providing essential information without redundancy, making it efficiently structured and appropriately sized for a simple tool.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is largely complete. It explains what the tool does and when to use it. However, it could be slightly more complete by hinting at the response format (e.g., list of endpoints with operationIds), though this is a minor gap for such a simple tool.

    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 input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description does not mention any parameters, which is appropriate since none exist. It adds value by explaining the tool's purpose and usage, compensating for the lack of parameter documentation in the schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the specific action ('List all available endpoints') and resource ('in the Swagger Petstore - OpenAPI 3.0'), distinguishing it from the sibling tool 'call_endpoint' which would execute operations rather than list them. The phrase 'Call this first to discover what operations are available' reinforces its distinct discovery purpose.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description explicitly provides usage guidance: 'Call this first to discover what operations are available and get their operationIds.' This indicates when to use this tool (as an initial discovery step) and implicitly suggests an alternative (using 'call_endpoint' once operations are known), making it clear in context with the sibling tool.

    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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