What are the prerequisites for installation?
Node.js v16 or higher and npm or yarn are required.
@Augmented-Nature
基本情報
A comprehensive Model Context Protocol (MCP) server providing advanced access to the UniProt protein database.
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"augmented-nature-uniprot-mcp-server-augmented-nature": {
"command": "docker",
"args": [
"build",
"-t",
"uniprot-mcp-server",
"."
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
An MCP server that provides 26 specialized bioinformatics tools for accessing the UniProt protein database via its REST API, enabling AI assistants and MCP clients to perform protein research, comparative genomics, structural biology, and systems biology analyses.
Install Node.js v16+, clone the repository, run npm install and npm build, then start with npm start or add the server to an MCP client (e.g., Claude Desktop) using the JSON configuration provided. Docker deployment is also supported: build the image with docker build -t uniprot-mcp-server and run with docker run -i uniprot-mcp-server.
Node.js v16 or higher and npm or yarn are required.
Add the following to your MCP client config: `{"mcpServers": {"uniprot": {"command": "node", "args": ["/path/to/build/index.js"], "env": {}}}}`.
It integrates with the UniProt REST API (`https://rest.uniprot.org`), setting a User-Agent header (`UniProt-MCP-Server/1.0.0`) and a 30‑second timeout.
Results can be returned in JSON, TSV, FASTA, or XML format, depending on the tool.
Yes. You can build a Docker image and run it with `docker run -i uniprot-mcp-server`, or use Docker Compose for easier management.

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