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reactome-db-mcp

reactome-db-mcp

by tc2fh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

schema_overview

Understand the Reactome GKB schema through a primer covering class-table-inheritance, useful tables, and join recipes before writing SQL queries.

Instructions

Explain the Reactome GKB schema so you can write correct SQL.

Returns a primer on the class-table-inheritance model (the `DatabaseObject`
supertable, subclass tables sharing `DB_ID`, the `Class_2_attribute` link
tables, and the stable-id join), the most useful tables, key join recipes,
and the data release loaded. **Read this once before writing `query()` SQL.**
The same primer is also available as the `schema://reactome` MCP resource.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "schema_overview"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

No annotations exist, so the description carries full burden. It describes the return content comprehensively (primer on class-table-inheritance, useful tables, join recipes, data release). For a read-only explanation tool, this is transparent; no destructive behavior is expected.

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 concise (three sentences) and well-structured: purpose first, then contents, then usage directive. Every sentence adds value without verbosity.

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 no parameters or output schema, the description is self-contained. It fully explains what the tool returns and mentions the data release loaded and the alternative resource. No gaps for an explanation tool.

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?

There are no parameters; baseline is 4. The description adds value by detailing what the tool explains, but no parameter documentation is needed.

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 tool's purpose: explaining the Reactome GKB schema to enable writing correct SQL. It uses specific verbs ('explain') and resources ('schema'), and distinguishes from siblings like describe_table and query.

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?

Explicit usage guidance is provided: 'Read this once before writing `query()` SQL.' This tells the agent when to use the tool and implies it as a prerequisite for querying. It also mentions an alternative source (schema://reactome resource).

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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