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Rdkit Mcp Server

mcp-tandemai-inc-rdkit-mcp-server · by tandemai-inc

MCP server that enables language models to interact with RDKit through natural language

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Install

$ agentstack add mcp-tandemai-inc-rdkit-mcp-server

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

RDKit MCP Server: Agentic Access to RDKit for LLMs

RDKit MCP Server is an open-source MCP server that enables language models to interact with RDKit through natural language. The goal is to provide agent-level access to every function in RDKit 2025.3.1 without writing any code.

Features

  • Seamless Integration: Exposes RDKit functions via the Model Context Protocol (MCP).
  • Language Model Support: Connect any LLM that supports the MCP protocol.
  • CLI Client: Includes a command-line client powered by OpenAI for quick experimentation.

Table of Contents

  • [Installation](#installation)
  • [Usage](#usage)
  • [Start the Server](#start-the-server)
  • [CLI Client](#cli-client)
  • [Available Tools](#available-tools)
  • [Evaluations](#evaluations)
  • [Contributing](#contributing)

Installation

Install the package:

pip install .

Usage

Start the Server

python run_server.py [--settings settings.yaml]

See settings.example.yaml for setting options

Once the server is running, any MCP-compliant LLM can connect. For example, see the Claude Desktop quickstart.

CLI Client

A CLI client is included for rapid prototyping with OpenAI:

export OPENAI_API_KEY="sk-proj-xxx"
python run_client.py

Available Tools

List all available RDKit tools exposed by the server:

python list_tools.py [--settings settings.yaml]

Evaluations

The evals directory contains a test suite for evaluating RDKit MCP tool outputs and agent responses using pydantic-evals.

Install Dependencies

pip install ".[evals]"

Start the MCP Server

In one terminal, start the server:

python run_server.py

Run Evaluations

In another terminal, run the evaluation suite:

python evals/run_evals.py

Options:

  • --verbose - Show detailed output including inputs and outputs
  • --filter - Run only cases matching the name
  • --output-json results.json - Export results to JSON

Each test uses LLM-based evaluation (LLMJudge) to assess whether the agent correctly used the RDKit tools and produced accurate results.

Contributing

We welcome contributions, feature requests, and bug reports:

See CONTRIB.md for guidelines on how to get started.

Together, we can make RDKit accessible to a wider range of applications through natural language interfaces.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.