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stedwick

codecov-mcp-server

by stedwick
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v0.1.5

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion between tools. The tool's purpose is clear and unambiguous.

    Naming Consistency5/5

    The single tool name 'get_commit_coverage_totals' follows a clear verb_noun pattern and is descriptive. With only one tool, consistency is trivially satisfied, but the name itself is well-formed.

    Tool Count2/5

    One tool is far too thin for a Codecov MCP server, which typically would need multiple operations (commits, branches, reports, etc.). The server appears to be scoped too narrowly.

    Completeness2/5

    The tool only provides commit coverage totals with file breakdown. Many obvious Codecov features are missing (e.g., coverage by branch, pull request, or trend analysis), creating significant gaps for most use cases.

  • Average 3.7/5 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 ISC 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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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior3/5

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

    With no annotations, the description carries the full burden of behavioral disclosure. It states the tool 'returns' data, which indicates a read-only operation, but it does not mention error handling, authentication requirements, or what happens if the commit is not found. This is minimal but sufficient for a simple read operation.

    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, clear sentence that directly conveys the tool's purpose. It is concise and front-loaded, with no wasted words or redundant information.

    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?

    The tool has no parameters, no output schema, and no annotations, so the description must stand alone. It explains what is returned (coverage totals and breakdown by file) but does not clarify how the commit is identified or what the response structure looks like. This leaves the tool's usage context incomplete.

    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 is empty, so the baseline is 4. However, the description references 'a given commit' without providing any parameter or context for how the commit is specified. This introduces ambiguity and suggests a parameter that does not exist, which detracts from the value of the description.

    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: returning Codecov coverage totals for a commit, broken down by file. The verb 'returns' and the specific resource 'coverage totals' make the purpose unambiguous. It is distinct from potential siblings by focusing on commit-level coverage totals.

    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 use cases for retrieving commit coverage totals but provides no explicit guidance on when to use this tool versus alternatives. Since no sibling tools are listed, the lack of exclusion or alternative references is not critical, but the description could be clearer about the intended context (e.g., for a specific commit in a CI pipeline).

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

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

Our badge communicates server capabilities, safety, and installation instructions.

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