# mcp-mondo

> mcp-mondo — pipeworx-io-mcp-mondo. Use this tool when you need to resolve condition strings onto a standardized disease ontology, enabling accurate and efficient mapping of disease terms. It solves problems of inconsistent disease terminology and facilitates data integration across different sources. The tool takes condition strings as input and outputs resolved terms mapped to the Mondo Disease Ontology.

Canonical page: https://skillsregistry.net/skills/pipeworx-io-mcp-mondo  
JSON: https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-mondo

## Description

Mondo — condition-string resolver onto the Mondo Disease Ontology.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/pipeworx-io/mcp-mondo)

## 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": "pipeworx-io-mcp-mondo"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-mondo` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-mondo/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