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bfernandez2-seidor

ccv2-logs-mcp

by bfernandez2-seidor
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TypeScript

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no ambiguity. The agent will always select search_logs for any log-related task.

    Naming Consistency5/5

    Single tool follows a clear verb_noun pattern (search_logs), consistent with MCP conventions.

    Tool Count3/5

    A single tool for log searching is borderline. While it covers the core function, a typical logging server might benefit from additional tools for listing sources or filtering by context.

    Completeness3/5

    The tool provides basic log search but lacks obvious features like log source enumeration, time-range filtering beyond what is implicit, or multi-aspect queries. This may cause agent failures for complex log retrieval tasks.

  • Average 3.8/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 26 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.

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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

  • Behavior3/5

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

    With no annotations, the description must carry behavioral burden. It mentions the newest-first ordering but not whether the operation is read-only, what happens on errors, or rate limits. The schema indicates no destructive side effects, but the description could be more explicit.

    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?

    Two concise sentences cover the main points without extraneous information. The description is front-loaded with the action and resource.

    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 8 parameters and no output schema, the description adequately conveys the purpose and key output fields. It lacks details on pagination and time range syntax, but the schema covers parameters thoroughly.

    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 coverage is 100%, so parameters are well-documented in the schema. The description adds no extra meaning to the parameters beyond listing output fields, which is unrelated.

    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 runtime logs in SAP CCv2 Cloud Logging, specifies the output format (newest-first log lines with specific fields), and uniquely identifies the resource and verb.

    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?

    No explicit guidance on when to use this tool versus alternatives. Since there are no sibling tools, the absence is less critical, but some hints on typical use cases or limitations would improve it.

    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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