@TakumiY235
基本信息
MCP server for UniProt protein data access
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"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
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.
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.
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.
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`.
All protein data is fetched live from the UniProt public API. A local cache (OrderedDict‑based) stores responses for 24 hours to improve performance.
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.
The server runs over stdio (configured as a command in Claude Desktop). No authentication is required because it queries the public UniProt API.
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