DecimerMCPServer
mcp-name: io.github.DocMinus/decimer-mcp-server
MCP server that exposes DECIMER image-to-SMILES functionality as tool calls.
This project is a thin adapter over the existing FastAPI service in DecimerServerAPI.
It does not run DECIMER models directly.
The adapter sends JSON requests by default, with automatic fallback to form payloads for compatibility.
Tools
server_health: Checks whether the DECIMER FastAPI server is reachable.analyze_chemical_image: Sends a base64-encoded image to/image2smiles/and returns structured output.
Requirements
- Python 3.10+
- Running DECIMER API server (default:
http://localhost:8099)
find it at either of these two versions:
- GitHub: https://github.com/DocMinus/DecimerServerAPI
- Dockerhub: https://hub.docker.com/r/docminus/decimer_api
Install
cd /Users/a/dev/DecimerMCPServer
uv venv
uv sync
Configuration
Copy .env.example values into your environment:
DECIMER_API_BASE_URL(defaulthttp://localhost:8099)DECIMER_API_TIMEOUT_SECONDS(default60)DECIMER_MAX_IMAGE_BYTES(default10000000)DECIMER_MCP_LOG_LEVEL(defaultINFO)
Run (stdio transport)
uv run decimer-mcp-server
or
uv run python -m decimer_mcp_server
Example MCP client config
{
"mcpServers": {
"decimer": {
"command": "uv",
"args": ["run", "python", "-m", "decimer_mcp_server"],
"env": {
"DECIMER_API_BASE_URL": "http://localhost:8099"
}
}
}
}
Output shape
analyze_chemical_image returns:
{
"ok": true,
"smiles": "CCO",
"reason": null,
"api_status_code": 200,
"api_message": null,
"classifier_score": 0.0000012,
"classifier_threshold": 0.3,
"classifier_decision": "structure_like"
}
When no SMILES is returned by API classifier behavior:
{
"ok": true,
"smiles": null,
"reason": "not_chemical_structure",
"api_status_code": 200,
"api_message": "No SMILES returned by API",
"classifier_score": 0.99999,
"classifier_threshold": 0.3,
"classifier_decision": "not_structure_like"
}
Development tests
uv sync --extra dev
uv run pytest
Make targets:
make sync
make test
Smoke test helper
Run one health check + one inference call against your DECIMER API:
cd /Users/a/dev/DecimerMCPServer
DECIMER_API_BASE_URL=http://chitchat:8099 uv run decimer-mcp-smoke-test --image /Users/a/dev/DecimerServerAPI/example_usage/structure.png
If you keep settings in .env, load it with:
uv run --env-file .env decimer-mcp-smoke-test --image /Users/a/dev/DecimerServerAPI/example_usage/structure.png
or use make:
make smoke
Override the image path if needed:
make smoke SMOKE_IMAGE=/absolute/path/to/image.png
## MCP Registry publishing
Tags matching `v*` trigger `.github/workflows/publish-mcp.yml`.
Workflow steps:
- installs `mcp-publisher`
- validates `server.json`
- calls registry publish using secret `MCP_REGISTRY_TOKEN`
- publishes slug `io.github.DocMinus/decimer-mcp-server` (case sensitive; must match registry grant)
Before tagging:
1. Update `pyproject.toml` + `server.json` versions
2. Ensure `server.json` stays valid (`uv pip install jsonschema && python validate snippet from AGENTS.md`)
3. Add GitHub repo secret `MCP_REGISTRY_TOKEN` (GitHub PAT with `repo`, `workflow` scopes)
Release flow:
```bash
git tag v0.1.1
git push origin v0.1.1
Monitor Actions tab. If publish fails, rerun using workflow dispatch after fixing issues.
## Contribution
This project was built by DocMinus with AI-assisted coding support (OpenCode/Copilot-style tooling), then reviewed and tested by the author.
## AI usage policy
- AI assistance was used for scaffolding, implementation drafts, and documentation edits.
- Final technical decisions, validation runs, and acceptance were performed by the maintainer.
- Runtime behavior should be validated with local tests (`make test`) and smoke tests (`make smoke`) before release.