# metabo-idmapper

> metabo-idmapper — wooyoung-kim91-metabo-idmapper. Use this tool when you need to standardize and integrate metabolite data from various sources, converting ambiguous names into consistent database identifiers. It solves problems of data inconsistency and incompatibility by crosswalking identifiers across KEGG, HMDB, ChEBI, PubChem, and InChIKey databases, as well as Mouse-GEM for metabolic modeling. The tool takes messy metabolite names as input and outputs standardized identifiers, making it ideal for applications requiring precise metabolic data integration and analysis.

Canonical page: https://skillsregistry.net/skills/wooyoung-kim91-metabo-idmapper  
JSON: https://api.skillsregistry.net/v1/skills/wooyoung-kim91-metabo-idmapper

## Description

Converts messy metabolite names into standard database identifiers (KEGG, HMDB, ChEBI, PubChem, InChIKey) and performs crosswalking to Mouse-GEM for metabolic model input, with deterministic tools and an LLM reasoning layer for identity disambiguation.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ww8x3o9e86)
- **Repository:** <https://github.com/Wooyoung-kim91/metabo-idmapper>

## 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": "wooyoung-kim91-metabo-idmapper"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/wooyoung-kim91-metabo-idmapper` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/wooyoung-kim91-metabo-idmapper/pull`

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