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.