Protein Structure MCP Server
Searches UniProt by protein name to find accession numbers and retrieves detailed protein structure information from AlphaFold, including direct links to 3D structural predictions.
README
Protein Structure Server
An MCP (Model Context Protocol) server that retrieves protein information by searching UniProt for accession numbers based on human protein names, then leverages AlphaFold to provide detailed protein data and direct links to AlphaFold structural predictions.
Features
- 🔍 Search proteins by name - Find proteins with prioritization of human proteins
- 🧬 Get detailed protein structure information - Retrieve comprehensive protein data from UniProt and AlphaFold
- 📊 Get UniProt accession numbers - Convert protein names to UniProt IDs
- 🌐 AlphaFold integration - Direct links to 3D protein structure predictions
Installation
Prerequisites
Setup
- Clone the repository:
git clone https://github.com/soffelcopter/protein_structure_MCP_server.git
cd protein_structure
- Install dependencies:
uv sync
Usage
Connecting to Claude Desktop
To use this server with Claude Desktop, you need to configure it in your Claude Desktop settings:
-
Open Claude Desktop and go to Settings > Developer > Edit Config
-
Add the protein structure server to your configuration:
{
"mcpServers": {
"protein_structure": {
"command": "uv",
"args": [
"run",
"--directory",
"/absolute/path/to/your/protein_structure",
"python",
"protein_structure_server.py"
]
}
}
}
Important: Replace /absolute/path/to/your/protein_structure with the actual absolute path to your project directory.
-
Restart Claude Desktop completely
-
Once connected, you can ask Claude to search for proteins, get structure information, and more! This can look like this:
<img src="assets/example.gif" alt="Protein Structure Server Example" width="800">
Testing with Model Inspector
For testing and debugging your server independently, use the MCP Inspector:
# Navigate to your server directory
cd protein_structure
# Start the model inspector
npx @modelcontextprotocol/inspector uv run python protein_structure_server.py
The Model Inspector provides a web-based interface to test your MCP server tools directly, helping you understand whether your tools are working as expected before integrating with Claude Desktop.
Available Tools
1. search_proteins(protein_name: str)
Search for proteins by name, with human proteins prioritized.
Example:
# Search for insulin proteins
search_proteins("insulin")
2. get_protein_structure(uniprot_accession: str)
Get detailed information about a protein including structure data from AlphaFold.
Example:
# Get insulin structure information
get_protein_structure("P01308")
3. get_uniprot_id(protein: str)
Get the UniProt accession number for a protein name.
Example:
# Get UniProt ID for insulin
get_uniprot_id("insulin")
API Integration
This server integrates with:
- UniProt REST API - For protein metadata and sequence information
- AlphaFold Database API - For protein structure predictions and PDB file links
Acknowledgments
- UniProt for protein sequence and annotation data
- AlphaFold Database for protein structure predictions
- MCP for the protocol implementation
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.