RDKit Tools MCP Server
A Model Context Protocol (MCP) server exposing core RDKit cheminformaticsoperations as tools, for use by AI agents (e.g. DIAL toolsets).
Complements other chemistry MCPs (SMILES visualization, ChEMBL database access) by covering thein-process cheminformatics operations they don't: descriptor/fingerprint calculation, similarity andsubstructure search, reaction enumeration, standardization, and 3D conformer generation.
Tools
| Tool | Description |
|---|---|
canonicalize_smiles |
Parse a SMILES string, return its canonical form and basic identity info |
standardize_molecule |
Clean up a molecule: strip salts/solvents, keep the largest fragment, neutralize charges |
calculate_descriptors |
Compute descriptors (MolWt, LogP, TPSA, HBD/HBA, ring counts, QED, ...) for one SMILES |
batch_calculate_descriptors |
Same, for a batch of SMILES |
calculate_fingerprint |
Compute a fingerprint (morgan, rdkit, or maccs) and return its on-bit indices |
tanimoto_similarity |
Tanimoto similarity between two molecules |
similarity_search |
Rank candidate SMILES by similarity to a query molecule |
substructure_search |
Check which candidates match a SMARTS substructure pattern |
enumerate_reaction |
Apply a reaction SMARTS/SMIRKS template to reactants, return distinct products |
generate_3d_conformer |
Generate (optionally force-field optimized) 3D conformers as MOL blocks |
Running locally
pip install -r requirements.txt
python server.py --host 127.0.0.1 --port 8080
Docker
docker build -t rdkit-tools-mcp .
docker run -p 8080:8080 rdkit-tools-mcp
The server speaks MCP over HTTP Streamable transport at /mcp.
