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reactome-mcp

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by reactome

reactome_cypher_schema

Introspect the Reactome graph schema to get labels, relationships, properties, indexes, and constraints before writing Cypher queries.

Instructions

Introspect the Reactome graph schema — labels with node counts, relationship types with cardinalities, per-label and per-rel property types (with mandatory flags), indexes, and constraints. Fetched live from the database via APOC on first call and cached in-memory for the rest of the session (~100–300 ms one-time). Call this before writing Cypher. For the full JSON (including the raw apoc.meta.schema() object), read the reactome://graph/schema resource.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description carries full responsibility and does it well. It discloses that the data is 'fetched live from the database via APOC on first call,' cached in-memory for the session, and has a '~100–300 ms one-time' cost. This gives the agent essential behavioral expectations about performance and side effects (no mention of writes, indicating read-only).

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 three sentences, each earning its place: the first defines the tool's output, the second covers performance/caching semantics, and the third gives usage timing plus a pointer for full JSON. No filler or redundancy—excellent conciseness and front-loading.

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?

Despite having no output schema, the description provides a detailed enumeration of the returned data (labels, relationship types, cardinalities, property types, mandatory flags, indexes, and constraints). It also explains how the data is fetched and cached, and when to call it. This is sufficient for an agent to decide when to invoke it and what to expect, especially given the tool has no parameters.

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?

With zero parameters, the input schema is trivially covered (100%), so the description need not explain parameter syntax. The baseline of 4 applies, and the description adds no unnecessary param info while correctly focusing on the tool's output and behavior.

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 uses a specific verb 'Introspect' with a clear resource ('Reactome graph schema') and enumerates the exact content delivered: labels with counts, relationship types with cardinalities, property types, mandatory flags, indexes, and constraints. This clearly distinguishes it from sibling tools like reactome_cypher_query and reactome_cypher_sample, which focus on querying data rather than schema inspection.

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 guidance is given: 'Call this before writing Cypher.' This tells the agent exactly when to invoke this tool. Additionally, it provides an alternative for a different need: 'For the full JSON... read the reactome://graph/schema resource.' This is clear, actionable, and distinguishes when to use the tool versus another 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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