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sirjebbington

mcp-server-starrocks

Read Query

read_query

Execute SQL SELECT queries on StarRocks to fetch data, optionally writing large results to a file for easier handling.

Instructions

Execute a SELECT query or commands that return a ResultSet. Set output_file to write the full result to disk instead of returning it inline (useful for large results).. Use set_session_db to set a per-session default database

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dbNodatabase
queryYesSQL query to execute
output_fileNoIf set, write the full result to this file and return only a summary + small preview inline. Relative paths resolve against STARROCKS_MCP_OUTPUT_DIR (default: ~/.mcp-server-starrocks/output/). Absolute paths (and ~) are used as-is. Format is inferred from the file extension (.csv, .tsv, .json, .jsonl, .ndjson) unless output_format is given. NOTE: the file is written on the server's filesystem, which may not be the client machine in remote/http deployments.
output_formatNoOverride file format: csv|tsv|json|jsonl. If omitted, inferred from output_file extension; defaults to csv.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden of behavior. It does disclose that the tool executes result-returning commands and can write large results to disk, which are relevant side-effects. However, it does not cover auth, rate limits, error behavior, or definitively state that non-SELECT (write) commands are unsupported, leaving some transparency gaps.

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?

The description is short and front-loaded with the core purpose. The second sentence adds practical suggestions that relate to parameter usage, but it is slightly marred by a double period and could be tightened into cleaner separate clauses.

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?

The 4-parameter tool is fully covered by an exhaustive schema, but with no output schema or annotations, the description still leaves room for incompleteness. It does mention output file behavior but doesn't describe what inline results look like overall, pagination, response size capture, or any limitations, which an agent may need before relying on this 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 description coverage is 100%, and the description adds no meaning beyond repeating output_file's disk-write behavior. Since schema handles parameter meaning, the baseline of 3 is correct: the description overlays nothing new for the parameters.

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 starts with a clear action, 'Execute a SELECT query or commands that return a ResultSet', which specifies the resource and differentiates this tool from write_query and analysis-tool siblings. The scoping to SELECT-like commands makes its read-oriented purpose unambiguous.

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 guidance on when to use output_file (large results) and points to set_session_db for per-session defaults. It doesn't explicitly say 'use write_query for writes', but the SELECT requirement implies a read-only context, giving agents enough direction though without an explicit exclusion.

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