EOSC-Data-Commons/data-commons-mcp

🔭 EOSC Data Commons MCP server

A Model Context Protocol (MCP) server exposing an HTTP POST endpoint to access data from various open-access data publishers, developed for the EOSC Data Commons project.

It uses a search API, and a Large Language Model (LLM) to help users find the datasets and tools they need.

🧩 Endpoints

The HTTP API comprises 2 main endpoints:

• /mcp: MCP server that searches for relevant data to answer a user question using the EOSC Data Commons OpenSearch service

  • Uses rmcp with Streamable HTTP transport
  • Available tools:
    • Search datasets
    • Search tools
    • Search citations related to datasets or tools

• /chat: HTTP POST endpoint (JSON) for chatting with the MCP server tools via an LLM provider (API key provided through env variable at deployment)

  • Uses axum, utoipa for OpenAPI spec generation, llm to interact with LLM providers (e.g. Mistral, OpenAI)
  • Returns a streaming response: tool call requested, then tool call results, and final search results.

🛠️ Development

[!IMPORTANT]

Requirements:

• Rust
• API key for a LLM provider: Mistral.ai or OpenAI, you can use the free tier, you just need to login

Recommended VSCode extension: rust-analyzer

📥 Install dev dependencies

rustup update
cargo install cargo-release cargo-deny cargo-watch git-cliff

Create a .cargo/config.toml file with your Mistral API key or OpenAI API key:

[env]
MISTRAL_API_KEY = "YOUR_API_KEY"
OPENAI_API_KEY = "YOUR_API_KEY"
EINFRACZ_API_KEY = "YOUR_API_KEY"

⚡️ Start dev server

Start the MCP server in dev at http://localhost:8000/mcp, with OpenAPI UI at http://localhost:8000/docs

cargo run

Customize server configuration through CLI arguments:

cargo run --  --mcp-only -b 0.0.0.0:8004 --opensearch-url http://localhost:9200

Run and reload on change to the code:

cargo watch -x run

[!NOTE]

Example curl request:

curl -X POST http://localhost:8000/chat -H "Content-Type: application/json" -H "Authorization: SECRET_KEY" -d '{"messages": [{"role": "user", "content": "data insulin"}], "model": "mistralai/mistral-small-latest", "stream": true}'

Recommended model per supported provider:

• openai/gpt-4.1
• mistralai/mistral-large-latest
• groq/moonshotai/kimi-k2-instruct
• einfracz/qwen3-coder

To build and integrate the frontend web app to the server, from the frontend folder run:

npm run build && rm -rf ../data-commons-mcp/src/webapp/ && cp -R dist/spa/ ../data-commons-mcp/src/webapp/

🔌 Connect MCP client

Follow the instructions of your client, and use the /mcp URL of your deployed server (e.g. http://localhost:8000/mcp)

🐙 VSCode GitHub Copilot

Add a new MCP server through the VSCode UI:

• Open the Command Palette (ctrl+shift+p or cmd+shift+p)
• Search for MCP: Add Server...
• Choose HTTP, and provide the MCP server URL http://localhost:8000/mcp

Your VSCode mcp.json should look like:

{
    "servers": {
        "data-commons-mcp-server": {
            "url": "http://localhost:8000/mcp",
            "type": "http"
        }
    },
    "inputs": []
}

📦 Build for production

Build binary in target/release/

cargo build --release

[!NOTE]

Start the server with:

./target/release/data-commons-mcp

🐳 Deploy with Docker

Create a keys.env file with the API keys:

MISTRAL_API_KEY=YOUR_API_KEY
SEARCH_API_KEY=SECRET_KEY_YOU_CAN_USE_IN_FRONTEND_TO_AVOID_SPAM

[!TIP]

SEARCH_API_KEY can be used to add a layer of protection against bots that might spam the LLM, if not provided no API key will be needed to query the API.

You can use the prebuilt docker image ghcr.io/eosc-data-commons/data-commons-mcp:main

Example compose.yml:

services:
  mcp:
    image: ghcr.io/eosc-data-commons/data-commons-mcp:main
    ports:
      - "127.0.0.1:8000:8000"
    environment:
      RUST_LOG: info
      OPENSEARCH_URL: "http://opensearch:9200"
      MISTRAL_API_KEY: "${MISTRAL_API_KEY}"

Build and deploy the service:

docker compose up

🧼 Format & lint

Automatically format the codebase using rustfmt:

cargo fmt

Lint with clippy:

cargo clippy --all

Automatically apply possible fixes:

cargo clippy --fix

⛓️ Check supply chain

Check the dependency supply chain: licenses (only accept dependencies with OSI or FSF approved licenses), and vulnerabilities (CVE advisories).

cargo deny check

Update dependencies in Cargo.lock:

cargo update

🏷️ Release

Dry run:

cargo release patch

Or minor / major

Create release:

cargo release patch --execute