UniProt MCP Server

Name: UniProt MCP Server
Author: TakumiY235

@TakumiY235

代码仓库

关于 UniProt MCP Server

MCP server for UniProt protein data access

基本信息

分类

其他

许可证

MIT

运行时

python

传输方式

stdio

发布者

TakumiY235

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "uniprot-mcp-server": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "-r",
        "requirements.txt"
      ]
    }
  }
}

工具

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概览

What is UniProt MCP Server?

A Model Context Protocol (MCP) server that provides access to UniProt protein information. It allows AI assistants to fetch protein function and sequence data directly from the UniProt database.

How to use UniProt MCP Server?

Install Python 3.10 or higher, clone the repository, and install dependencies with uv pip install -r requirements.txt or pip install -r requirements.txt. Then add the server configuration (command: uv, args pointing to the directory and run uniprot-mcp-server) to your Claude Desktop config file. Once configured, you can ask Claude to retrieve protein information by providing UniProt accession numbers.

Key features of UniProt MCP Server

Fetch protein info by single UniProt accession
Batch retrieval of multiple proteins
Built‑in caching with a 24‑hour TTL
Error handling for invalid accessions, network issues, and rate limits
Returns protein name, function, full sequence, length, and organism

Use cases of UniProt MCP Server

Quickly look up the function and sequence of a protein during research
Compare multiple proteins side‑by‑side (e.g., P04637 and P02747)
Integrate UniProt data into AI‑powered bioinformatics workflows

FAQ from UniProt MCP Server

What does this server do that alternatives don’t?

It exposes UniProt protein data through the Model Context Protocol, allowing AI assistants like Claude to directly fetch structured protein information (name, function, sequence, organism) without requiring a separate API call or manual parsing.

What are the runtime dependencies?

Python 3.10 or higher, the MCP Python SDK, and httpx for async HTTP requests. Use uv (recommended) or pip to install dependencies listed in requirements.txt.

Where does the data come from, and is it cached?

All protein data is fetched live from the UniProt public API. A local cache (OrderedDict‑based) stores responses for 24 hours to improve performance.

Are there any known limits or error scenarios?

The server handles invalid accession numbers (404), network errors, rate limiting (429), and malformed responses. Caching has a 24‑hour TTL and size limits are managed internally.