# omop_mcp

> omop_mcp — ohnlp-omop-mcp. Use this tool when you need to map clinical terminology to standardized concepts, such as Observational Medical Outcomes Partnership (OMOP) concepts, to facilitate data analysis and research. It solves problems of inconsistent terminology and data integration by utilizing Large Language Models to generate accurate mappings. The omop_mcp tool takes clinical terms as input and outputs corresponding OMOP concepts, enabling seamless data exchange and comparison across different healthcare systems.

Canonical page: https://skillsregistry.net/skills/ohnlp-omop-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ohnlp-omop-mcp

## Description

Model Context Protocol (MCP) server for mapping clinical terminology to Observational Medical Outcomes Partnership (OMOP) concepts using Large Language Models

## Trust

- **Trust score (0–1):** 0.80
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** maps-location
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/OHNLP/omop_mcp)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "ohnlp-omop-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ohnlp-omop-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ohnlp-omop-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt