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mcp-ubergraph-query

mcp-ubergraph-query

by twhetzel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_term_info

Retrieve detailed information about an ontology term, including labels, definitions, synonyms, and types, with optional hierarchy details.

Instructions

Get comprehensive information about a specific ontology term (labels, definitions, synonyms, types).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "curie": "<curie>"
    },
    "name": "get_term_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
curieYesOntology term CURIE (e.g., 'MONDO:0005015', 'HP:0001945')
include_hierarchyNoInclude immediate parent and child terms

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations exist. The description implies a read operation but does not disclose specific behavioral traits (e.g., auth requirements, rate limits, or side effects). It is straightforward but minimal.

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 a single sentence of 15 words, clearly and efficiently communicating the tool's purpose without extraneous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple input (2 params) and no output schema, the description adequately covers what the tool returns. It could list more return fields, but it includes key examples (labels, definitions).

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 parameters are well-documented. The description adds no new meaning beyond the schema; it merely restates that the term is an ontology term.

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 retrieves comprehensive information about a specific ontology term (labels, definitions, synonyms, types). It distinguishes from siblings: get_hierarchy (hierarchy), query_ubergraph (graph queries), search_terms (search).

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?

The description provides no guidance on when to use this tool compared to alternatives like get_hierarchy or query_ubergraph. It does not specify scenarios or prerequisites.

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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