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andychinghk01

db-query-mcp

by andychinghk01
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct roles: list_db for discovery and query for executing SQL. There is no overlap in their purposes or outputs.

    Naming Consistency4/5

    Both tools use a verb-first pattern, but list_db is verb_noun while query is just a verb. This is a minor deviation and still predictable.

    Tool Count3/5

    With only 2 tools, the set feels thin, though each earns its place for the stated read-only query purpose. The count is at the lower boundary of typical MCP servers.

    Completeness5/5

    The tool surface fully covers the domain of read-only database querying: listing available databases and executing arbitrary SELECT/SHOW/DESCRIBE/EXPLAIN statements. No critical gaps exist.

  • Average 4.1/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 2 commits in the last 12 weeks
    • 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

  • Behavior3/5

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

    With no annotations, the description carries the full burden. The verb 'List' implies a safe, read-only operation, but the description does not explicitly state side effects, permission requirements, or any operational constraints. It provides minimal behavioral context beyond the basic function, which is adequate but not comprehensive.

    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, focused sentence that immediately states the action and key output details. It contains no fluff or redundant information, making it highly concise and well-structured for quick agent reading.

    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?

    The tool is very simple (no parameters, no output schema), and the description covers the core operation and output. It does not mention return value format or any limitations, but given the low complexity, the description is largely sufficient. Sibling differentiation is minimal, slightly reducing completeness.

    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 baseline is 4. The description need not explain parameter semantics, and the input schema (empty) confirms that no parameters exist. The description adds no unnecessary param details, which 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's function with a specific verb ('List') and resource ('configured MySQL and PostgreSQL databases'), and specifies the output fields (names, types, descriptions). This distinguishes it from the sibling tool 'query', which likely executes queries rather than enumerating databases.

    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 usage: use this tool to see available databases. However, it does not explicitly mention when not to use it or contrast with the sibling 'query' tool. There is no direct guidance on alternative tools, so it falls short of a clear 'when to use vs alternatives' explanation.

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

  • Behavior4/5

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

    No annotations are provided, but the description carries the burden by specifying the tool is read-only and enumerating allowed statement types (SELECT/SHOW/DESCRIBE/EXPLAIN). It also mentions parameterized values with placeholder syntax for MySQL/PostgreSQL, giving useful behavioral context. It doesn't describe output format, but for a query tool this is sufficient.

    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, front-loaded with the core purpose, and no redundant information. Every sentence contributes meaning, making it an efficient description.

    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?

    The description covers the key aspects for a moderate-complexity tool: read-only constraint, allowed statements, and parameterization. It lacks an explicit mention of the result format, but given no output schema and the straightforward nature of a query tool, it is sufficiently complete.

    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 parameter descriptions already documenting sql, dbName, and params. The description additionally reinforces the read-only constraint and clarifies that dbName is as shown by list_db, but doesn't add significant new semantics beyond the schema. 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 executes read-only SQL queries (SELECT/SHOW/DESCRIBE/EXPLAIN) against a MySQL/PostgreSQL database, using a specific verb and resource. It distinguishes itself from sibling list_db, which lists databases, by focusing on query execution.

    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?

    It clearly implies usage for read-only querying against a chosen database, referencing list_db for database selection. However, it doesn't explicitly state 'use this instead of list_db when you need to retrieve data,' making it a clear context but without explicit exclusionary guidance.

    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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