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PeterGreenAppliedAI

FlowMCP

by PeterGreenAppliedAI
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Server Quality Checklist

67%
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  • Latest release: v0.3.0

  • Disambiguation3/5

    The tools overlap: morning_brief includes the top 5 HN stories, so both tools can satisfy a request for HN top stories. However, the descriptions clearly distinguish when to use each: hn_top for immediate HN queries and morning_brief for a broader daily summary. This overlap creates some ambiguity, but the usage cues help.

    Naming Consistency4/5

    Both tool names follow a consistent pattern of lowercase noun phrases with underscores (hn_top, morning_brief). While they don't use verb_noun naming, the style is predictable and coherent across the set, with no mixed conventions.

    Tool Count3/5

    With only 2 tools, the set is on the thin side, but it matches the server's narrow purpose of providing a morning briefing and HN top stories. The count is borderline but not unreasonable for such a small scope.

    Completeness4/5

    For the apparent domain of news and weather summaries, the core workflows are covered. A minor gap is the lack of a standalone weather-only tool, but the combined briefing handles the main use case. The surface is largely complete for its stated purpose.

  • Average 4.4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 59 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

  • 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?

    Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the output format ('markdown list') and the fixed count ('top 5 stories'), which is mildly useful, but it does not disclose any additional behavioral traits such as rate limits, authentication, or network dependencies.

    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 extremely concise, using three short clauses to convey when to use, what it returns, and that it takes no parameters. Every sentence earns its place and the key trigger is front-loaded with WHEN TO USE.

    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 simple, parameterless, read-only tool with strong annotations, the description fully covers the trigger condition, the output content, and the output format. No additional context is necessary for an agent to select and invoke the tool correctly.

    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 tool has zero parameters, so the schema already fully describes the input contract. The description explicitly states 'Takes no parameters,' reinforcing the schema and providing a baseline score of 4 as per rubric guidance.

    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 returns the top 5 Hacker News stories as a markdown list, with a specific verb ('Returns') and resource. It also includes a concrete trigger condition ('the user asks what is on Hacker News right now'), which distinguishes it from the sibling tool morning_brief.

    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 explicitly provides a WHEN TO USE condition, making the intended usage clear. However, it does not mention when not to use it or mention alternatives such as morning_brief, so it misses the highest bar for usage guidance.

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

  • Behavior5/5

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

    The description adds valuable behavioral context beyond the annotations: it specifies the output is a single markdown brief, includes today's weather and exactly 5 HN stories, and notes 'No API keys needed.' This is useful, and it does not contradict the readOnly/openWorld hints.

    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 sentences, with the WHEN TO USE trigger front-loaded. Every sentence conveys essential information: when to use, what it returns, and a notable constraint (no API keys). No wasted 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?

    For a simple tool with one optional parameter and no output schema, the description is largely complete. It covers the trigger, the content of the brief, and a key operational detail. It could mention the exact format of the markdown (e.g., headings) or pagination, but for this scope it is sufficient.

    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 already provides 100% coverage for the one parameter (city) with a clear description. The tool description only repeats this by saying 'today's weather for a city,' adding no new semantic information. 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 tool returns a markdown brief with today's weather for a city plus the top 5 Hacker News stories. This specific verb+resource combination distinguishes it from the sibling hn_top, which likely focuses solely on HN stories.

    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 opens with an explicit WHEN TO USE condition: 'the user asks for a morning briefing or daily summary.' It provides clear context, though it does not explicitly mention when NOT to use it (e.g., if only HN stories are requested, hn_top might be more appropriate).

    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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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.

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