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mathewsls

postgres-explorer

by mathewsls
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: execute_query handles arbitrary SELECT queries, while get_schema retrieves metadata about tables and columns. No overlap or ambiguity exists.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (execute_query, get_schema) using snake_case, making the naming predictable and clear.

    Tool Count2/5

    With only 2 tools, the server feels minimal for a 'PostgreSQL explorer'. Typical exploration would benefit from additional tools like describe_table, list_schemas, or view_details, making 2 tools insufficient for a well-scoped exploration surface.

    Completeness3/5

    The server covers basic schema browsing and arbitrary read queries, but lacks more granular tools (e.g., specific table details, constraint info, index listing). Users cannot easily explore beyond the public schema or get metadata about individual objects without writing SQL.

  • Average 3.8/5 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

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  • 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 provided, yet description only mentions it's for SELECT and returns results no details on errors, permissions, row limits, or what happens on write attempts. Incomplete for a critical tool.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Two concise sentences front-load the purpose. Could be slightly improved by structuring parameter details.

    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 only one parameter and an output schema, the description is missing parameter semantics and behavioral details, which are needed for safe usage.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0% and description adds no explanation for the sql parameter, leaving it completely undefined.

    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?

    Clearly states it executes a SQL SELECT query on PostgreSQL and returns results. Differentiates from sibling tool get_schema.

    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 says 'use only for read queries', providing context on when to use it. No explicit alternatives mentioned but sibling is get_schema.

    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?

    The description correctly implies a read-only operation by stating it retrieves schema information. With no annotations providing safety hints, the description carries the burden and adequately communicates the non-destructive nature. However, it omits details like permissions or side effects, which are likely negligible for a schema retrieval tool.

    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, clear sentence with no fluff. Every word earns its place, and it is front-loaded with the core action. Conciseness is excellent.

    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 that the tool has no parameters and an output schema exists (though not provided), the description is complete enough. It clearly states the output (list of tables and columns) and context (public schema of PostgreSQL). No additional details are necessary for this straightforward tool.

    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?

    There are no parameters, so the schema coverage is 100%. The description does not add meaning beyond the empty schema, but for zero-parameter tools, a baseline of 4 is appropriate as the schema already fully defines the interface.

    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 retrieves a list of tables and columns from the public schema of PostgreSQL. The verb 'obtiene' (gets) and resource 'tablas y sus columnas' are specific, and it distinguishes itself from the sibling tool 'execute_query' which likely 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 Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    While the description implies this tool is for exploring schema structure rather than executing queries (given the sibling), it does not explicitly state when to use it or when not to use alternatives. No exclusions or alternatives are mentioned.

    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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