uniprot-mcp

GitHub repo: fzlzjerry/uniprot-mcp · PyPI package & command: uniprotkb-mcp (the Python import package is uniprot_mcp).

A production-quality MCP server that exposes the UniProt REST API to LLM clients (Claude Code, Claude Desktop, …) over stdio. Built with FastMCP and managed with uv.

Tools return compact, token-efficient summaries by default and full payloads only on request, with robust error handling and an embedded UniProt query cheat-sheet so the model writes valid queries.

Published on PyPI — no clone, no install needed:

uvx uniprotkb-mcp

Then point your MCP client at it (full config below):

{
  "mcpServers": {
    "uniprot": {
      "command": "uvx",
      "args": ["uniprotkb-mcp"],
      "env": { "UNIPROT_MCP_CONTACT": "you@example.org" }
    }
  }
}

Plus an MCP resource resource://uniprot/query-cheatsheet documenting the UniProtKB query syntax (gene:, organism_id:, reviewed:true, length:[X TO Y], keyword:, ec:, boolean AND/OR/NOT, …).

• Python ≥ 3.10 (the repo pins 3.13 via .python-version)
• uv

git clone https://github.com/fzlzjerry/uniprot-mcp
cd uniprot-mcp
uv sync                 # creates .venv and installs fastmcp + httpx

# stdio server (what MCP clients launch):
uv run uniprotkb-mcp

UniProt asks API clients to identify themselves with a contact address. Set one via the UNIPROT_MCP_CONTACT environment variable (it goes into the User-Agent); otherwise a placeholder is used.

UNIPROT_MCP_CONTACT="you@example.org" uv run uniprotkb-mcp

uvx (a.k.a. uv tool run) fetches, builds, and runs the console script in a throwaway environment — nothing to install first. Pick whichever source you have:

# From PyPI (published):
uvx uniprotkb-mcp

# From a Git repo (note: repo is uniprot-mcp, command is uniprotkb-mcp):
uvx --from git+https://github.com/fzlzjerry/uniprot-mcp uniprotkb-mcp

# From a local checkout (this directory):
uvx --from /ABSOLUTE/PATH/TO/uniprot-mcp uniprotkb-mcp

# From a built wheel:
uvx --from ./dist/uniprotkb_mcp-0.1.0-py3-none-any.whl uniprotkb-mcp

Pin a version with uvx uniprotkb-mcp@0.1.0, or force a refresh of the cached build with uvx --refresh --from <source> uniprotkb-mcp.

Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%\Claude\claude_desktop_config.json) and add:

{
  "mcpServers": {
    "uniprot": {
      "command": "uvx",
      "args": ["uniprotkb-mcp"],
      "env": { "UNIPROT_MCP_CONTACT": "you@example.org" }
    }
  }
}

This runs the published package straight from PyPI. To run unreleased code instead, add a source: "args": ["--from", "git+https://github.com/fzlzjerry/uniprot-mcp", "uniprotkb-mcp"] (git) or "args": ["--from", "/ABSOLUTE/PATH/TO/uniprot-mcp", "uniprotkb-mcp"] (local checkout). Make sure uvx is on the PATH Claude Desktop sees (it ships with uv; give the absolute path to uvx if needed, e.g. ~/.local/bin/uvx). Restart Claude Desktop and the uniprot tools appear.

Prefer a cloned checkout instead of uvx? Use "command": "uv", "args": ["run", "--directory", "/ABSOLUTE/PATH/TO/uniprot-mcp", "uniprotkb-mcp"].

Project-scoped via a .mcp.json in your project root (same shape):

{
  "mcpServers": {
    "uniprot": {
      "command": "uvx",
      "args": ["uniprotkb-mcp"],
      "env": { "UNIPROT_MCP_CONTACT": "you@example.org" }
    }
  }
}

Or from the CLI:

# via uvx (published / git / local source):
claude mcp add uniprot -e UNIPROT_MCP_CONTACT=you@example.org -- uvx uniprotkb-mcp

# via a local checkout with uv:
claude mcp add uniprot -e UNIPROT_MCP_CONTACT=you@example.org \
  -- uv run --directory /ABSOLUTE/PATH/TO/uniprot-mcp uniprotkb-mcp

Exercises every tool against the live API and prints the output:

UNIPROT_MCP_CONTACT="you@example.org" uv run python -m tests.smoke

Developing, testing, CI, and the release process (CI-driven PyPI Trusted Publishing — no token) are documented in CONTRIBUTING.md. TL;DR: uv sync, then uv run python -m tests.check_structure (offline) and uv run python -m tests.smoke (live API).

• Single shared httpx.AsyncClient with a descriptive User-Agent including your contact.
• Retry/backoff on 429 (honoring Retry-After) and 5xx; 400 surfaces UniProt's own error message; no raw tracebacks reach the client (errors are raised as ToolError).
• Pagination via the Link header / x-total-results; result sizes are capped (≤ 500) and the total is always reported so you can narrow or page.
• ID mapping follows the real async flow: POST /idmapping/run → poll /idmapping/status/{job} (a 303 + Location signals completion) → fetch results, automatically choosing the enriched UniProtKB results endpoint vs. the simple-pair endpoint based on the target database.

src/uniprot_mcp/
  server.py       # FastMCP instance, the 7 tools, cheat-sheet resource, main()
  client.py       # shared AsyncClient, retry/backoff, error mapping, header parsing
  idmapping.py    # async run/poll/results flow with target-aware routing
  config.py       # cached idmapping db config + from/to validation
  formatting.py   # JSON -> compact summary digests
  cheatsheet.py   # UniProt query cheat-sheet
tests/smoke.py    # live-API smoke test