mgnify-mcp

MGS-sails/mgnify-mcp

3.1

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The MGnify MCP Server provides access to MGnify resources and tools via the Model Context Protocol, enabling seamless integration with MCP-compatible clients.

MGnify MCP Server

This repository implements an MCP server that exposes MGnify resources and tools over the Model Context Protocol.

Prerequisites

  • Python 3.10+ recommended (the mcp SDK requires Python >= 3.10). The project metadata uses a marker to skip installing mcp on older Python, but the server cannot run without it.
  • pip >= 21
  • Optional: Docker

Quick start (Python 3.10+)

  1. Create and activate a virtual environment

    • macOS/Linux: python3 -m venv .venv source .venv/bin/activate
    • Windows (PowerShell): py -3.10 -m venv .venv .venv\Scripts\Activate.ps1

  2. Install the package (editable) and dependencies pip install -e .

  3. Configure environment (optional)

    • Copy .env.example to .env and adjust values as needed cp .env.example .env
    • Available variables:
      • MG_BASE_URL: Override the MGnify API base URL (default: https://www.ebi.ac.uk/metagenomics/api/v1)
      • MG_API_KEY: If you have an API token, it will be sent as Bearer auth
      • BIND, PORT: Only used if you enable the HTTP transport in server.py

  4. Optional: Run a local smoke test (no MCP client needed) python scripts/smoke_test.py

    • This will call the MGnify API via the included client to ensure things work locally.

  5. Run the MCP server (stdio transport) mgnify-mcp

    • The server will run over stdio until the client disconnects. Use an MCP-compatible client/tooling to connect.

Using with Claude Desktop (example)

  • Add to your claude_desktop_config.json or the UI where MCP servers are configured: { "mcpServers": { "mgnify": { "command": "/path/to/venv/bin/mgnify-mcp", "env": { "MG_BASE_URL": "https://www.ebi.ac.uk/metagenomics/api/v1" } } } } Replace the command with the absolute path to your venv script.

Alternative: Docker

  • Build docker build -t mgnify-mcp .
  • Run (stdio is not practical via docker). If you want HTTP transport, uncomment serve_http in mgnify_mcp/server.py and rebuild, then: docker run --rm -p 8173:8173 --env-file .env mgnify-mcp Then configure your client to connect to http://localhost:8173

Troubleshooting

  • pip cannot find mcp / versions ignored require Python >=3.10 Upgrade to Python 3.10 or newer. The server relies on the mcp SDK.
  • SSL or network errors to MGnify API Check MG_BASE_URL and your network. The public API should be reachable without an API key; some endpoints may rate-limit.
  • Rate limiting The server surfaces 429 as an error with retry-after from MGnify. Back off and retry.

Development tips

  • Run unit/lint tools you prefer. The code uses Pydantic v2 for input schemas and Requests for HTTP.
  • Entry point is defined in pyproject.toml: mgnify-mcp -> mgnify_mcp.server:main