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nandanosql

database-explorer-mcp

by nandanosql

export_data

Export database query results as CSV or JSON for portable data transfer and analysis.

Instructions

Export query results as CSV or JSON format. Useful for getting data out of the database in a portable format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows (default: 100, max: 1000)
queryYesSQL query or MongoDB JSON query
formatNoOutput format (default: csv)
connectionNoConnection alias (default: 'default')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It discloses format options and portability but omits critical traits: whether export writes files server-side or returns content, read-only vs mutation, permission requirements, row-limit behavior, and error handling.

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 sentences, front-loaded with the action and formats. The second sentence is slightly padding but not harmful, so the definition remains appropriately concise.

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?

For a four-parameter tool with no output schema and no annotations, the description leaves too much unspecified. An agent cannot tell whether export_data returns inline data, a file path, or writes to disk, nor how it relates to run_query.

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 description coverage is 100%, so all four parameters are documented in the schema. The description only echoes the CSV/JSON format enum and adds no syntax, default, connection-alias, or limit detail beyond what the schema already provides.

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 (export) and resource (query results) plus supported formats (CSV/JSON). It does not differentiate from sibling run_query, which also executes queries, but the export framing is clear enough to identify the tool's core action.

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?

No explicit when-to-use, prerequisites, or alternatives are provided. The second sentence is generic and does not tell an agent when to choose export_data over run_query or search_data.

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