mcp-data-agent

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run_query

Execute a single read-only SELECT query with row limits and timeout protection to safely explore database data while blocking writes, DDL, and multiple statements.

Instructions

Run a single read-only SELECT query.

Writes, DDL, multiple statements and SQL comments are rejected. Results are capped at 100 rows and queries time out after 5 seconds.

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": {
      "sql": "<sql>"
    },
    "name": "run_query"
  }
}

Input Schema

Name	Required	Description	Default
`sql`	Yes
`row_limit`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 23, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses read-only enforcement, rejected statement classes, a 100-row cap, and a 5-second timeout. It omits what happens on rejection (error shape) and any permission/auth requirements, which are relevant for a query 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?

Four short sentences, front-loaded with the core action, then constraint bullets. Every sentence carries a distinct operational fact with no waste.

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?

An output schema exists, so return values needn't be described, and the operational limits (rows, timeout, rejected SQL) cover the main behavioral risks. The remaining gap is the interaction between the documented row cap and the undocumented row_limit parameter.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate, but it never mentions the 'sql' syntax expectations or the existence of 'row_limit'. Worse, the stated 100-row cap creates ambiguity about whether row_limit can override it. Only the implicit cap is conveyed, leaving both parameters materially unexplained.

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 opens with a specific verb and resource ('Run a single read-only SELECT query') and establishes scope ('single') that cleanly separates it from list_tables and describe_table. An agent can tell what this tool does without opening the 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?

The description defines the boundary clearly: writes, DDL, multiple statements and comments are rejected, which tells the agent when NOT to use it. It stops short of naming the sibling tools as alternatives for common needs like listing tables.

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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