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fastmcp-me

mcp-server-duckdb

by fastmcp-me
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Server Quality Checklist

67%
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  • Latest release: v1.1.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion between tools. The 'query' tool has a single, unambiguous purpose of executing DuckDB queries.

    Naming Consistency5/5

    The single tool name 'query' is a clear, straightforward verb that accurately describes its function. With only one tool, naming consistency is trivially satisfied.

    Tool Count3/5

    One tool is on the thin side for a full database server like DuckDB. While a generic query tool can cover many operations, it lacks typical helper tools (e.g., schema listing, table inspection) that agents might expect, making the count borderline.

    Completeness4/5

    The query tool can execute any SQL, enabling full CRUD and DDL operations, so there are no direct dead ends. However, there is no built-in schema discovery or validation, which is a minor gap that agents can work around via SQL queries against system tables.

  • Average 3.5/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • No commit activity data available
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • 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

  • Behavior2/5

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

    No annotations are provided, so the description carries full responsibility for disclosing behavioral traits. It only states that a query is executed, without mentioning whether it is read-only, what it returns, or any side effects. This lacks important behavioral context.

    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, concise sentence that is front-loaded and contains no extraneous information. Every word earns its place.

    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?

    Given the simplicity of the tool (one parameter, no output schema), the description is minimally adequate. However, it does not explicitly state the return behavior or any constraints, which would be helpful for a query tool.

    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 fully describes the sole parameter ('SQL query to execute'), so schema coverage is 100%. The description adds no additional parameter-level meaning, resulting in baseline score of 3.

    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 that the tool executes a query on DuckDB, using a specific verb ('execute') and resource ('DuckDB database'). It unambiguously identifies the tool's function without relying on the tool name alone.

    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 does not provide explicit when-to-use or alternative guidance, but the intended usage is implied: it is used to run SQL queries on DuckDB. This matches the 'implied usage' level rather than having no guidance at all.

    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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  • Evaluate tool definition quality.

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