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rawtreedb

RawTree MCP Server

Official
by rawtreedb

Run Query

run-query

Execute read-only SQL queries on RawTree data to retrieve JSON rows, column metadata, and query statistics. Use for data exploration, verification, and aggregations.

Instructions

Purpose: Execute a read-only SQL query against the configured RawTree project and return JSON rows, column metadata, statistics, and hints.

NOT for: Inserting, updating, deleting, or mutating data. RawTree validates queries as read-only and rejects unsafe statements.

Returns: RawTree's query response: meta, data, rows, statistics, and optional hints.

When to use:

  • User asks questions about data already in RawTree

  • You need to verify an insert

  • You need a quick aggregate, sample, or schema-oriented SELECT

  • You need RawTree query hints after an error

Workflow: Start with a bounded SELECT. For exploratory queries, include LIMIT and order by a time column when available.

Key trigger phrases: "query RawTree", "run SQL", "count rows", "show sample rows", "check the data"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesRead-only SQL to execute. Prefer bounded SELECT queries with LIMIT for exploration.
Behavior5/5

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

Since no annotations are provided, the description fully discloses that the tool is read-only, validates queries, rejects unsafe statements, and returns a specific response structure.

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 well-organized with clear sections, concise sentences, and front-loaded critical information. Every sentence provides value without redundancy.

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?

Given the single parameter and no output schema, the description covers purpose, restrictions, usage patterns, and workflow hints comprehensively.

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?

The input schema already describes the sql parameter, but the description adds context like recommending bounded SELECT with LIMIT and ordering by time. This adds value beyond the schema.

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 purpose: execute a read-only SQL query and return results. It distinguishes from mutation tools by explicitly noting it is not for inserting, updating, or deleting.

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?

Provides explicit 'NOT for' section and lists specific use cases (user questions, verify insert, quick aggregate, etc.). Additionally includes trigger phrases for agent selection.

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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