# chem-research-mcp

> chem-research-mcp — tjkessler-chem-research-mcp. Use this tool when you need to accelerate chemical research by leveraging a literature-based RAG (Retrieval-Augmented Generator) model trained on open combustion, QSAR, and fuel-chemistry papers. It solves problems related to information retrieval and knowledge discovery in chemical research, providing relevant outputs to user queries. Input your research questions through a browser or integrate with Cursor/Claude Desktop for streamlined access to chemical insights.

Canonical page: https://skillsregistry.net/skills/tjkessler-chem-research-mcp  
JSON: https://api.skillsregistry.net/v1/skills/tjkessler-chem-research-mcp

## Description

MCP server + literature RAG over open combustion / QSAR / fuel-chemistry papers. Ask in the browser or wire Cursor / Claude Desktop to the same tools.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/tjkessler/chem-research-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": "tjkessler-chem-research-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/tjkessler-chem-research-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/tjkessler-chem-research-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