Install
$ agentstack add mcp-tandemai-inc-rdkit-mcp-server ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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.
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.
- Author: tandemai-inc
- Source: tandemai-inc/rdkit-mcp-server
- License: MIT
- Homepage: https://tandemai.com
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.