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Marholoubek

Health MCP Server

by Marholoubek
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    With only a single tool, there is no possibility of ambiguity between tools. The purpose of 'list_adapters' is clear and distinct by default.

    Naming Consistency5/5

    The single tool name 'list_adapters' follows a consistent verb_noun pattern, which is clear and predictable. No inconsistencies exist due to the singular tool.

    Tool Count2/5

    The server has only one tool, which feels insufficient for a server branded as 'Health MCP Server'. The scope appears extremely narrow, and a health-related server would typically require multiple tools to be useful (e.g., data retrieval, management).

    Completeness1/5

    The tool surface is severely incomplete. A health server should include tools for querying health data, managing adapters (add/remove/update), and possibly filtering or analyzing data. The single 'list_adapters' tool covers only a trivial subset of expected functionality.

  • Average 4.4/5 across 1 of 1 tools scored.

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • 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?

    No annotations are provided, so the description must disclose behavioral traits. 'List' suggests a read-only operation, which is transparent, but the description does not explicitly state it is non-destructive or mention any rate limits or authentication requirements.

    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 concisely conveys the tool's purpose and the information it provides. No extraneous words.

    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 simplicity (no parameters, no siblings, no output schema), the description is mostly complete. It covers what the tool does and what data it returns, though it could benefit from mentioning the output format or any default behaviors.

    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 zero parameters, so schema coverage is 100%. The description adds no parameter information beyond what is already known, which is acceptable for a parameterless tool.

    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 identifies the action 'list' and the resource 'health data adapters' with the specific attribute 'authentication status'. There are no sibling tools, so differentiation is not required.

    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 implies that the tool is used to retrieve a list of all adapters, but does not explicitly state when to avoid using it or alternatives. Since there are no sibling tools, the lack of exclusions is acceptable.

    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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