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mahAnuj

mcp-multi-db

by mahAnuj
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Server Quality Checklist

67%
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  • Latest release: v1.0.2

  • Disambiguation5/5

    Each tool has a distinct purpose: describing a table's schema, listing database connections, listing tables in a database, and executing read-only queries. No overlap between tools.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in lower_snake_case (describe_table, list_databases, list_tables, run_query). Perfectly uniform.

    Tool Count5/5

    With 4 tools, the server covers essential database exploration tasks without being bloated or too sparse. The count is appropriate for a read-only multi-database interface.

    Completeness4/5

    The set covers discovering databases, listing tables, describing schemas, and running SELECT queries. Missing are write operations, but they are intentionally blocked. A minor gap is lack of a tool to view recent queries or metadata beyond column types, but core workflow is solid.

  • Average 3.9/5 across 4 of 4 tools scored. Lowest: 3.3/5.

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

    • No community issues in the last 6 months
    • 9 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under ISC License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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, but description does not disclose behavioral traits like read-only nature, authentication needs, or side effects. Minimal information beyond the basic action.

    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?

    Single sentence is concise and front-loaded with key verb and object. No wasted words, but could be more structured.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    No output schema; description does not explain return format (e.g., array of names). Parameters are covered, but the result is missing, making it incomplete for a listing 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?

    Schema coverage is 100% with descriptions for both 'database_id' and 'schema'. Description adds no additional meaning beyond what schema already provides, 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?

    Description clearly states verb 'List', resource 'tables and views', and context 'in a configured database'. This distinguishes it from siblings like 'describe_table' (which describes a specific table) and 'list_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?

    Implied usage: use after selecting a database. No explicit when-to-use, when-not-to-use, or alternatives beyond sibling names.

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

  • Behavior2/5

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

    No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states 'describe columns' with no mention of side effects, permissions, error handling, or return format, leaving significant gaps for a read-like operation.

    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 with no wasted words, front-loading the core action and target.

    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 absence of an output schema and low complexity, the description adequately identifies the tool's purpose but lacks details about what the tool returns (e.g., column names, types), which would improve completeness.

    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%, so the input schema already documents each parameter with descriptions. The tool description adds no additional meaning beyond the schema, meeting the baseline expectation.

    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 action ('describe columns') and the resource ('table in a configured database'), distinguishing it from sibling tools like list_databases (list databases), list_tables (list tables), and run_query (execute arbitrary SQL).

    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 when column details of a specific table are needed, but provides no explicit guidance on when to prefer this tool over alternatives like run_query, nor any 'when not to use' scenarios.

    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?

    With no annotations, the description must disclose behavior. It clearly states the tool is read-only and blocks writes, a critical safety trait. It does not mention return format or error handling, but for a simple 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?

    The description is a single sentence with no redundant information. It front-loads the key action and constraint, earning 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, high schema coverage, and absence of output schema, the description is mostly complete. It could mention the result format (e.g., JSON array) but omission is minor.

    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%, so the description adds no extra semantic meaning beyond the schema definitions for database_id, sql, and limit. It does not explain parameter interdependencies or formatting rules.

    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 verb 'Execute' and the resource 'read-only SQL query on a configured database'. It also explicitly blocks writes, distinguishing it from siblings like describe_table and list_databases which provide metadata.

    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 provides clear context by specifying allowed SQL commands (SELECT, WITH, EXPLAIN) and forbidding writes. It does not explicitly list alternative tools for non-query needs, but the sibling list implies usage boundaries.

    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?

    No annotations exist, so description carries full burden. It describes a simple list operation (read-only) but does not explicitly state safety or idempotency. However, for a 0-param list tool, the default assumption of no side effects is reasonable.

    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?

    Single sentence front-loads action and output fields, with no wasted words. Efficient and clear.

    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 0-param discovery tool with no output schema, the description sufficiently covers what it returns and why to call it. No gaps.

    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?

    No parameters in schema, so schema coverage is 100%. The description adds value by listing returned fields and explaining purpose, making it a baseline 4.

    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 a specific verb 'List' and resource 'all configured database connections' with fields (id, type, label, description). It clearly differentiates from sibling tools like list_tables and describe_table by indicating this is the first call to discover database_id.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

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

    Explicitly states 'Call this first to discover which database_id to use', providing clear when-to-use guidance and implying it is a prerequisite for other tools.

    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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