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martoc

mcp-a2a-documentation

by martoc
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Python

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools are completely distinct: one searches for relevant documentation pages, the other retrieves the full content of a specific page. There is no overlap in their functionality.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern: search_documentation and read_documentation. The naming style is uniform and predictable.

    Tool Count3/5

    With only two tools, the server feels somewhat sparse. However, search and read are the core operations for documentation access, so the count is reasonable even though it falls at the low end of the typical range.

    Completeness4/5

    The tool surface covers the main workflow: discover pages via search, then fetch full content via read. A minor gap is the lack of a direct way to list all documents without performing a search, but this can be worked around.

  • Average 4.5/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 6 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • 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.

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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

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description carries the full burden. It discloses stemming behavior, the limitation that only 'a2a' is indexed, the maximum limit of 50, and the return format. This is solid transparency, though it could explicitly state that it is a read-only operation, which is implied by 'search'.

    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 concise and well-structured: a one-sentence summary, then a clear 'Args' section, and a 'Returns' section. Every sentence adds value, and the information is front-loaded.

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

    Completeness5/5

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

    For a search tool with no annotations and a simple schema, the description is complete. It covers purpose, all parameters, return format, and a key limitation (source only a2a). The presence of an output schema is noted, but the description still adequately describes the expected result fields.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description thoroughly explains each parameter beyond what the schema provides: query supports stemming, section has common values, source is currently only 'a2a', and limit has default/max. This fully compensates for the 0% schema description coverage.

    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 searches A2A protocol documentation by keyword, using a specific verb and resource. It distinguishes itself from the sibling read_documentation by focusing on searching rather than reading, making the purpose unmistakable.

    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 usage is implied: search when you need to find documentation by keyword. However, it does not explicitly compare with read_documentation or state when not to use this tool. The description offers context about sections and source, but lacks explicit exclusions or alternative guidance.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden. It discloses the return value (full markdown content) and error behavior (error message if not found). This is adequate transparency for a simple read tool, though it does not address permissions or other potential side effects.

    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 well-structured with Args and Returns sections. It is concise, front-loaded with the main purpose, and every sentence adds value without unnecessary fluff.

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

    Completeness5/5

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

    For a single-parameter tool with an output schema, the description is complete. It explains the path parameter, the return value, and error handling, covering all relevant aspects for effective invocation. There is no missing critical information.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema provides only a bare 'path' string with no description (0% coverage). The description compensates fully by explaining the path format (relative, prefixed with source name) and giving concrete examples, adding significant meaning beyond 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 tool's verb ('Read') and resource ('full content of a specific A2A protocol documentation page'). It distinguishes itself from the sibling tool 'search_documentation' by focusing on reading a specific page by path rather than searching.

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

    Usage Guidelines4/5

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

    The description provides clear context for usage by noting that the path is returned in search results, implying a workflow of search-then-read. However, it does not explicitly state when not to use this tool or mention alternatives beyond this implicit connection, so it falls short of a 5.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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