Skip to main content
Glama
musen-lab

CEDAR MCP Server

Official
by musen-lab

term_search_from_ontology

Search BioPortal across an entire ontology to find standardized names and IRIs for terms, using a search string and ontology acronym.

Instructions

Search BioPortal for standardized ontology terms within an entire ontology.

Use this tool to find the correct standardized name and IRI for a given term label across an entire ontology (not restricted to a specific branch).

Args: search_string: The term label or keyword to search for (e.g., "melanoma", "diabetes") ontology_acronym: Ontology acronym to search within (e.g., "NCIT", "CHEBI", "DOID")

Returns: Search results from BioPortal containing matching terms

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
search_stringYes
ontology_acronymYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that this is a search operation returning matching terms, but lacks details on result format, pagination, rate limits, or any potential side effects. This is minimally adequate for a search tool but not rich.

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 efficiently structured: a one-line summary, a 'Use this tool' context, and well-labeled Args/Returns sections. Every sentence earns its place, with no redundant phrases.

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 tool's simplicity and the presence of an output schema, the description covers purpose, scope, and parameters adequately. However, it could be more complete by mentioning behavior for no results or invalid ontology acronyms, though these are minor given the output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides only raw types with 0% description coverage, but the description includes an Args section that explains each parameter with examples ('melanoma', 'NCIT'). This fully compensates and adds meaning beyond the structured 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 opens with 'Search BioPortal for standardized ontology terms within an entire ontology', which specifies the verb, resource, and scope. It also explicitly notes 'not restricted to a specific branch', effectively distinguishing it from the sibling tool 'term_search_from_branch'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It states 'Use this tool to find the correct standardized name and IRI for a given term label across an entire ontology', giving clear context. The phrase '(not restricted to a specific branch)' implies when not to use it, but it does not explicitly name the alternative or provide strong exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/musen-lab/cedar-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server