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mcp-ubergraph-query

mcp-ubergraph-query

by twhetzel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

search_terms

Search for ontology terms by label or synonym to retrieve matching terms with their IDs.

Instructions

Search for ontology terms by label or synonym. Returns matching terms with their IDs.

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": {
      "text": "<text>"
    },
    "name": "search_terms"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesSearch text (label or synonym)
ontologiesNoFilter by ontology prefixes (e.g., ['MONDO', 'HP'])
limitNoMaximum results
exact_matchNoRequire exact match vs substring

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations exist, so the description must convey behavioral traits. It states the tool 'Returns matching terms' but does not disclose whether it is read-only, potential side effects, rate limits, or behavior for empty results. The description is too vague to ensure safe invocation.

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 two efficient sentences, front-loaded with the purpose. No extraneous information; every word serves a purpose.

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

Completeness2/5

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

With 4 parameters and no output schema, the description is insufficient. It does not explain the return format beyond 'IDs', lacks details on sorting, pagination, or error handling. Given sibling tools, more context could differentiate use cases.

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?

The input schema covers all 4 parameters with descriptions (100% coverage). The description adds no additional meaning beyond what the schema provides, so baseline 3 is appropriate.

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 'Search for ontology terms by label or synonym' with a specific verb and resource. It distinguishes from sibling tools (get_hierarchy, get_term_info, query_ubergraph) by focusing on term lookup, not hierarchy or graph queries.

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?

No guidance is provided on when to use this tool versus sibling tools. For example, it could mention that for detailed term info, use get_term_info. The description does not address context or exclusions.

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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