What are the prerequisites for installation?
Node.js v16 or higher and npm or yarn are required.
@Augmented-Nature
Basic information
A comprehensive Model Context Protocol (MCP) server providing advanced access to the UniProt protein database.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"augmented-nature-uniprot-mcp-server-augmented-nature": {
"command": "docker",
"args": [
"build",
"-t",
"uniprot-mcp-server",
"."
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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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