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ujwal-patel

Custom OpenAPI MCP Server

by ujwal-patel
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JavaScript
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool serves a distinct purpose: listing endpoints under a tag, describing a specific endpoint, and generating a request example. There's no overlap or ambiguity between them.

    Naming Consistency5/5

    All tool names follow a clear verb_noun pattern in snake_case: list_endpoints_by_tag, describe_endpoint, generate_request_example. This is perfectly consistent.

    Tool Count4/5

    Three tools is on the low end but still within the expected range for a focused server. It feels slightly thin for general OpenAPI exploration, but each tool earns its place.

    Completeness3/5

    The set covers tagged endpoint listing, detailed endpoint descriptions, and request example generation, but lacks a way to list available tags or all endpoints without a tag. This is a notable gap that could hinder agents unfamiliar with the API structure.

  • Average 3.5/5 across 3 of 3 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
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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  • This repository includes a README.md file.

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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 full responsibility for disclosing behavioral traits. It only states that it 'Return[s]' information, without mentioning read-only behavior, error conditions, or any side effects. This is insufficient for transparency.

    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 concise sentence (8 words) that is front-loaded and free of redundant information. It efficiently conveys the core function without unnecessary detail.

    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?

    For a simple tool with two parameters and no output schema, the description gives a general idea but lacks specifics about response structure or error handling. It is adequate given the tool's simplicity but not comprehensive enough to score higher.

    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 covers both parameters with clear descriptions and examples (e.g., /auth/login, POST). The tool description adds no additional meaning about parameters, so with 100% schema coverage, the baseline score of 3 is appropriate.

    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 tool's function: 'Return summary, description, parameters & responses for one endpoint.' The verb 'Return' and the specific resource 'one endpoint' make the purpose explicit, and it distinguishes from sibling tools like list_endpoints_by_tag (listing multiple endpoints) and generate_request_example (creating an example).

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

    Usage Guidelines3/5

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

    The description implies usage for a single endpoint ('for one endpoint') but does not explicitly state when to use this tool over alternatives or mention any exclusions. No direct guidance is given, so it only meets the 'implied usage' level.

    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. The 'if it has one' caveat hints at conditional behavior but does not explain what happens for endpoints without a body, error behavior, or the exact output format.

    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 sentence that is front-loaded with the core action and contains no filler. It is appropriately concise for a simple tool.

    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?

    For a simple two-parameter tool, the description conveys the main purpose, but without annotations or an output schema it leaves behavioral uncertainty (e.g., what happens for endpoints without a body, exact return value). Adequate but with notable gaps.

    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 already describes both parameters fully ('Endpoint path', 'HTTP verb'), and the description adds no additional parameter-level meaning. With 100% schema coverage, the baseline score of 3 is appropriate.

    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 function: generating a sample JSON body for a given endpoint. It uses a specific verb ('Create') and identifies the resource, distinguishing it from sibling list/describe tools.

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

    Usage Guidelines3/5

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

    Usage is implied: use when a sample JSON body for an endpoint is needed. There is no explicit guidance on when not to use it or how it relates to sibling tools, though the distinct purpose is inferable.

    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?

    With no annotations provided, the description carries the burden of behavioral disclosure. It states that the tool returns a list of methods and descriptions for all endpoints under a tag, which is transparent about the output shape. However, it does not mention any potential limitations (e.g., pagination, authentication requirements) or confirm non-destructive behavior beyond the word "List". The description provides basic transparency but no deeper behavioral context.

    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, front-loaded sentence that conveys the essential information without any filler. It is 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?

    For a tool with one well-documented parameter and no output schema, the description is complete: it states the input (tag) and the output (method + description for each endpoint). It lacks only optional details like pagination or ordering, but these are not essential for understanding the tool's core function. Given the presence of siblings, the description is sufficient to guide selection and 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?

    The schema fully documents the sole parameter "tag" with a clear description and example. Since schema coverage is 100%, the description adds little beyond the schema. The tool's description refers to "under a given tag", which reinforces the parameter's meaning but does not add new semantic detail. Baseline 3 is appropriate.

    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 action (List) and the resource (every endpoint under a given tag), and specifies the returned fields (method + description), distinguishing it from the sibling tools describe_endpoint and generate_request_example.

    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 a use case (listing endpoints by tag) but offers no explicit when-to-use guidance or alternatives, and fails to distinguish when to use this vs describe_endpoint or generate_request_example. No exclusions or context.

    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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