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mcp-bd-readonly

mcp-bd-readonly

by noemartinezoptima
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

run_query

Execute read-only SQL queries against a MySQL inventory and invoicing database and return JSON columns and rows, with optional row limits for safe data inspection.

Instructions

SQL solo-lectura; devuelve {columns, rows} (JSON). limit clamp filas (default 100; 0=sólo conteo, None=todo).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "run_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose the important traits: the query is read-only (safety profile), the return shape is {columns, rows}, and limit is clamped with special values. It omits error behavior, statement restrictions (single statement? dialect?), timeouts, and permission requirements, so it is only partially transparent.

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?

A single front-loaded sentence with zero filler; the read-only fact and return shape come first, limit semantics second. It is arguably over-terse for a 0%-coverage schema, but nothing is wasted.

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?

There is no output schema, and the description does cover the return shape, which is the main thing an agent needs. However, for a raw SQL execution tool with no annotations and 0% parameter documentation, the absence of dialect, permission, statement-count, and error-handling details leaves real gaps.

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 0%, so the description must compensate. It does well for limit, specifying clamping, default 100, 0 = count only, and None = all rows — genuinely more than the bare integer schema. The query parameter itself is only implied by 'SQL solo-lectura'; no dialect, statement count, or format guidance is given.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: executes read-only SQL and returns {columns, rows} as JSON. This distinguishes it from report-style siblings in kind (generic query vs. canned report), but it never explicitly contrasts itself with facturas_venta, resumen_iva, or the other domain tools, so the boundary is left to inference.

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

Usage Guidelines2/5

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

There is no when-to-use guidance. With twelve siblings including several canned financial reports and a describe_table tool, the agent gets no signal about when to reach for ad-hoc SQL versus a purpose-built report tool, nor any prerequisite or exclusion.

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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