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djgadd

node-sqlite-mcp

by djgadd
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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool serves a distinct purpose: listing tables, describing schema, and executing read-only queries. There is no functional overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (describe_table, list_tables, query). 'query' as a single verb is standard for SQL operations.

    Tool Count5/5

    Three tools are appropriate for a read-only SQLite explorer, covering the essential operations of listing, describing, and querying without unnecessary bloat.

    Completeness5/5

    The tool set fully covers the domain of exploring a SQLite database: listing tables/views, inspecting their schema, and running arbitrary read-only queries. No obvious gaps.

  • Average 4.4/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 7 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 passing

  • 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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 present, so the description fully discloses the output structure (columns, types, not-null, primary-key flags). It is honest about reading schema without side effects.

    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: first explains output, second clarifies parameter requirements. 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?

    No output schema, but description thoroughly explains return fields. For a simple schema-reading tool with 2 params, this 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?

    Schema coverage is 100% with both parameters well-described. The description adds minimal extra detail (path must be absolute), so 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 uses the specific verb 'describe' and clearly identifies the resource as 'schema of a single table or view'. It distinguishes from siblings: list_tables lists tables, query executes queries.

    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 clearly states what the tool does and implies when to use it. While it does not explicitly exclude alternatives, context signals provide sibling tools for contrast.

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

  • Behavior3/5

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

    Without annotations, the description carries the burden. It notes the path constraint but does not disclose error handling (e.g., if file not found), whether it is read-only, or the output format (just names). More detail would improve transparency.

    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 no redundant information. The purpose is stated first, followed by a necessary constraint. Every word earns its place.

    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 (one required parameter, no output schema), the description is largely complete. It could mention potential errors or what happens with invalid paths, but the basic functionality is covered.

    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 schema provides 100% coverage for the single parameter, and the description adds the critical context that the path must be absolute. This adds meaning beyond the schema's 'Absolute path to the SQLite database file.'

    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 lists names of tables and views in a SQLite database. It uses a specific verb ('List') and resource ('tables and views'), and the sibling tools ('describe_table', 'query') indicate distinct purposes.

    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 implicitly guides usage by specifying the 'path' must be an absolute filesystem path. It doesn't explicitly state when to use vs siblings, but the tool's purpose of listing tables is distinct from describing a table or querying.

    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?

    With no annotations, the description fully discloses behavior: read-only, TSV output, no truncation, single statement requirement, and cautions about large results. This covers key behavioral traits effectively.

    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 concise (4-5 sentences) and well-structured: first sentence states purpose and output, then constraints, then caution and parameter details. No unnecessary words.

    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?

    Given the tool's simplicity (2 params, no output schema, no annotations), the description is complete: it explains output format, constraints, cautions, and parameter requirements. It lacks only explicit error handling info, but that is minor.

    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?

    Schema coverage is 100%, so baseline is 3. The description adds value by clarifying that 'path' must be absolute and 'sql' must be a single statement, and provides an example of what to avoid (SELECT *). This enhances understanding beyond the schema.

    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 runs a read-only SQL query against a SQLite database and returns results as TSV. It distinguishes from sibling tools (describe_table, list_tables) which are for schema inspection, not arbitrary queries.

    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?

    Explicitly mentions read-only nature, that INSERT/UPDATE/DELETE fail, advises caution with broad queries, and specifies the need for absolute paths and single statements. Does not explicitly mention alternatives but strongly implies this tool is for ad-hoc queries.

    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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