home / mcp / chembl mcp server
A comprehensive Model Context Protocol (MCP) server providing advanced access to the ChEMBL chemical database.
Configuration
View docs{
"mcpServers": {
"augmented-nature-chembl-mcp-server": {
"command": "docker",
"args": [
"run",
"-i",
"chembl-mcp-server"
]
}
}
}The ChEMBL MCP Server provides programmatic access to the ChEMBL chemical database through a Model Context Protocol (MCP) server. It exposes a comprehensive suite of tools for chemical data retrieval, target analysis, bioactivity data, drug development insights, chemical property analysis, and advanced search capabilities, all designed to power AI assistants and MCP clients in drug discovery workflows.
You run the MCP server locally or via a container and connect your MCP client to it to perform tasks such as compound lookups, target queries, bioactivity exploration, and more. When you start the server, it communicates over standard input/output (stdio) so your MCP client can send requests and receive responses in real time. You can also run the server inside Docker and connect through the same MCP client interface.
# Prerequisites
- Node.js v16 or higher
- npm (or yarn)
# Local installation (build and run)
git clone <repository-url>
cd chembl-server
npm install
npm run build
npm start
```} ,{Search the ChEMBL database by compound name, synonym, or identifier.
Retrieve detailed information for a specific compound by ChEMBL ID.
Find compounds by InChI key or InChI string.
Retrieve chemical structure information in formats like SMILES, InChI, MOL, or SDF.
Identify chemically similar compounds using Tanimoto similarity.
Search for biological targets by name or type.
Retrieve detailed target information and annotations.
Get compounds tested against a specific target.
Find ChEMBL targets by UniProt accession numbers.
List biological pathways associated with targets.
Search bioactivity measurements and assay results.
Retrieve detailed assay information and conditions.
Find bioactivity data by activity type and value range.
Obtain dose-response data and activity profiles.
Compare bioactivity data across multiple compounds or targets.
Search for approved drugs and clinical candidates.
Retrieve drug development status and clinical trial information.
Search for therapeutic indications and disease areas.
Get mechanism of action and target interaction data.
Analyze ADMET properties (Absorption, Distribution, Metabolism, Excretion, Toxicity).
Calculate molecular descriptors and physicochemical properties.
Predict aqueous solubility and permeability properties.
Assess drug-likeness using Lipinski Rule of Five and related metrics.
Find compounds containing specific substructures.
Process multiple ChEMBL IDs efficiently.
Provide links to external databases (PubChem, DrugBank, PDB, etc.).
Perform complex queries with multiple chemical and biological filters.