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.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.