CovAiLent
An MCP server for chemistry-focused tools, enabling LLM agents to perform molecule parsing, format conversion, property lookup, and other chemistry operations with explainable responses.
README
CovAiLent
A Model Context Protocol (MCP) server for chemistry-focused tools with a focus on autonomy and explainability.
CovAiLent provides chemistry-related operations over the Model Context Protocol (MCP) so clients can query, transform, and reason about molecular information in a structured way.
Table of Contents
- Overview
- Features
- Architecture
- Quickstart
- Run with MCP Inspector
- Use with an MCP Host
- Configuration
- Repository Layout
- Examples
- Development
- Security Notes
- Roadmap
- Contributing
- License
Overview
Large language model agents often need domain-specific operations such as parsing molecules, converting formats, looking up properties, or planning laboratory tasks. CovAiLent exposes these operations through MCP, making them:
- Composable: usable from any MCP-compatible client or multi-agent framework.
- Auditable: responses return structured outputs with optional explanations.
- Portable: implemented in Python and can run locally or behind HTTPS/SSE.
Features
- Exposes chemistry operations as typed MCP tools with JSON-schema input and output.
- Provides resources such as reference data as MCP resources.
- Supports explainability options in responses.
- Offers multiple transports: STDIO for local use, HTTP(S)/SSE for deployment.
- Includes runnable examples and helper scripts.
Architecture
mcp_client (host/app)
│
├── STDIO (local development)
└── HTTP/SSE (remote/self-hosted)
│
┌─────┴─────────────────────────────┐
│ CovAiLent MCP Server │
│ • Tools: chemistry operations │
│ • Resources: reference data │
│ • Explainability: optional notes │
└───────────────────────────────────┘
Quickstart
Prerequisites
- Python 3.10+
- A virtual environment tool (
venv,uv, orconda) - Node.js (required if you use the MCP Inspector UI)
1) Clone and install
git clone https://github.com/Mod26y/CovAiLent.git
cd CovAiLent
python -m venv .venv && source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install -r requirements.txt
2) Run the server (STDIO)
python -m mcp_server
Some environments may expect:
python -m mcp_server stdio
Run with MCP Inspector
The MCP Inspector helps explore CovAiLent’s tools and schemas.
- Start the Inspector (Node.js required):
npx @modelcontextprotocol/inspector - In the UI, choose STDIO as transport and set the command to start this server:
python -m mcp_server - Connect and view the Tools tab to run CovAiLent tools.
Use with an MCP Host
Add CovAiLent as a custom MCP server in your host configuration. Example for Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"covailent": {
"command": "python",
"args": ["-m", "mcp_server"],
"env": {
// Optional: API keys or feature flags
// "COVAILENT_API_KEY": "...",
// "COVAILENT_ENABLE_EXPLANATIONS": "1"
}
}
}
}
Configuration
Environment variables supported at startup include:
| Variable | Purpose |
|---|---|
COVAILENT_ENABLE_EXPLANATIONS |
Include human-readable rationales in responses. |
COVAILENT_DEFAULT_TIMEOUT_MS |
Per-tool timeout in milliseconds. |
HTTP_PORT / HOST |
If running the HTTP/SSE server. |
LOG_LEVEL |
One of DEBUG, INFO, WARNING, ERROR. |
Repository Layout
.
├─ mcp_server/ # Server code (tools, resources, transports)
├─ examples/ # Demonstrations and scripts
├─ scripts/ # Development and helper scripts
├─ requirements.txt
├─ LICENSE # Apache-2.0
└─ README.md
Examples
See examples/ for end-to-end demonstrations:
- Tool discovery and execution
- Format conversion between chemical representations
- Property lookups and calculations
- Explainable responses
Run an example:
python examples/<example_name>.py
Development
Lint and test
pip install -r requirements.txt
# if available:
# make lint
# make test
Type checking
python -m pip install mypy
mypy mcp_server
HTTP/SSE (optional deployment)
If running with an HTTP app, for example:
uvicorn mcp_server.http:app --host 127.0.0.1 --port 8765
Security Notes
- MCP servers execute tools at request time. Run CovAiLent in a restricted environment and validate inputs.
- When exposing over HTTP/SSE, use authentication and restrict origins.
- Periodic security reviews are recommended before integrating into production agents.
Roadmap
- Additional chemistry tools and dataset resources
- Extended explainability options (structured traces)
- Provider integrations via environment variables
- Docker image for deployment
Contributing
Please open an issue to discuss proposed features or bug fixes before submitting a PR. The process is:
- Fork the repository and create a feature branch.
- Add tests or examples when appropriate.
- Ensure linting and type checks pass.
- Open a pull request with a clear description.
License
Apache License 2.0 © CovAiLent contributors. See LICENSE for details.
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