RDKit Tools MCP Server

A Model Context Protocol (MCP) server exposing core RDKit cheminformatics operations as tools, for use by AI agents (e.g. DIAL toolsets).

Complements other chemistry MCPs (SMILES visualization, ChEMBL database access) by covering the in-process cheminformatics operations they don't: descriptor/fingerprint calculation, similarity and substructure 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.