MCP server for DECIMER image-to-SMILES chemical structure recognition
{
"mcpServers": {
"io-github-docminus-decimer-mcp-server": {
"command": "<see-readme>",
"args": []
}
}
}No install config available. Check the server's README for setup instructions.
Are you the author?
Add this badge to your README to show your security score and help users find safe servers.
MCP server for DECIMER image-to-SMILES chemical structure recognition
Is it safe?
No package registry to scan.
No authentication — any process on your machine can connect.
License not specified.
Is it maintained?
Commit history unknown.
Will it work with my client?
Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
No automated test available for this server. Check the GitHub README for setup instructions.
No known vulnerabilities.
This server is missing a description. Tools and install config are also missing.If you've used it, help the community.
Add informationHave you used this server?
Share your experience — it helps other developers decide.
Sign in to write a review.
Persistent memory using a knowledge graph
Monitor browser logs directly from Cursor and other MCP compatible IDEs.
Privacy-first. MCP is the protocol for tool access. We're the virtualization layer for context.
Pre-build reality check. Scans GitHub, HN, npm, PyPI, Product Hunt — returns 0-100 signal.
MCP Security Weekly
Get CVE alerts and security updates for io.github.DocMinus/decimer-mcp-server and similar servers.
Start a conversation
Ask a question, share a tip, or report an issue.
Sign in to join the discussion.
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.
server_health: Checks whether the DECIMER FastAPI server is reachable.analyze_chemical_image: Sends a base64-encoded image to /image2smiles/ and returns structured output.http://localhost:8099)find it at either of these two versions:
cd /Users/a/dev/DecimerMCPServer
uv venv
uv sync
Copy .env.example values into your environment:
DECIMER_API_BASE_URL (default http://localhost:8099)DECIMER_API_TIMEOUT_SECONDS (default 60)DECIMER_MAX_IMAGE_BYTES (default 10000000)DECIMER_MCP_LOG_LEVEL (default INFO)uv run decimer-mcp-server
or
uv run python -m decimer_mcp_server
{
"mcpServers": {
"decimer": {
"command": "uv",
"args": ["run", "python", "-m", "decimer_mcp_server"],
"env": {
"DECIMER_API_BASE_URL": "http://localhost:8099"
}
}
}
}
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"
}
uv sync --extra dev
uv run pytest
Make targets:
make sync
make test
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 loc
... [View full README on GitHub](https://github.com/DocMinus/DecimerMCPServer#readme)