OHNLP/omop_mcp

Overview

Map clinical terminology to OMOP concepts using LLMs for healthcare data standardization and interoperability. Features include vocabulary search, batch processing, and domain-specific vocabulary prioritization.

Capabilities

• • resource handlers
• • prompt templates
• • github integration
• • mcp client integration

Best For

Tool for mapping clinical terms to OMOP concepts with LLMs, enabling healthcare data standardization and interoperability.

Decision Snapshot

• • GitHub stars: 34
• • Forks: 5
• • Source provenance count: 1
• • Active signal: Updated this week from lifecycle signals.
• • Last seen: 4/15/2026
• • Published: 3/16/2026

Features

• • **Mapping clinical terminology**: Intelligent mapping of free-text terms to standardized OMOP concepts.
• • **Vocabulary Search**: Direct access to OMOP vocabulary via find_omop_concept.
• • **Batch Processing**: Tool for mapping multiple concepts from a CSV file.
• • **Preferred Vocabularies**: Automatic domain-specific vocabulary prioritization (e.g., LOINC for measurements, SNOMED for conditions).
• • **Live Documentation**: Resource access to live OMOP CDM documentation.
• • resource handlers
• • prompt templates
• • github integration

Use Cases

• • Supports capabilities such as: resource handlers; prompt templates; github integration.
• • Common usage themes: mcp, curated, markdown-list, awesome-mcp-servers-punkpeye.

Supported Clients / Integrations

• • resource handlers
• • prompt templates
• • github integration
• • mcp client integration

Compatibility Signals

• • GitHub: supports (Detected in parser config/capability hints.)

Notes / Requirements

• • Primary language: Python
• • License: NOASSERTION
• • Documentation coverage: medium
• • Parser coverage score: 1.00
• • Source feeds: Awesome MCP Servers (punkpeye)
• • Topic cluster: general

Official Links

• Website
• Repository
• Documentation 1
• Documentation 2 (/uv/getting-started/ins...)

Source Information

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