AlphaFold-MCP-Server

Overview

The AlphaFold MCP Server provides extensive tools for protein structure analysis, including structure retrieval in multiple formats (PDB, CIF, BCIF, JSON), confidence score analysis, batch processing capabilities, and integration with visualization tools like PyMOL and ChimeraX. It enables researchers to efficiently access and analyze AlphaFold's vast collection of protein structure predictions. The server implements proper error handling and rate limiting to ensure stable interaction with the AlphaFold API.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

• get_structureuniprotId (required), format (optional)

  Retrieve AlphaFold structure prediction for a specific UniProt ID

  Try:Get the structure for protein P04637 in JSON formatTry:Fetch AlphaFold prediction for Q8N726 in PDB format
• download_structureuniprotId (required), format (optional)

  Download AlphaFold structure file in specified format

  Try:Download PDB file for protein P04637Try:Get BCIF format structure for Q8N726
• check_availabilityuniprotId (required)

  Check if AlphaFold structure prediction is available for a UniProt ID

  Try:Check if structure exists for P04637Try:Verify availability for protein Q8N726
• search_structuresquery (required), organism (optional), size (optional)

  Search for available AlphaFold structures by protein name or gene

  Try:Search for structures related to p53 proteinTry:Find all structures from Homo sapiens
• get_confidence_scoresuniprotId (required), threshold (optional)

  Get per-residue confidence scores for a structure prediction

  Try:Get confidence scores for protein P04637Try:Show residues with confidence above 80 for Q8N726
• batch_structure_infouniprotIds (required), format (optional)

  Get structure information for multiple proteins simultaneously

  Try:Get info for proteins P04637, P53350, and P63151Try:Retrieve summary data for multiple UniProt IDs
• compare_structuresuniprotIds (required)

  Compare multiple AlphaFold structures for analysis

  Try:Compare structures of P04637, P53350, and P63151Try:Analyze differences between proteins P12345 and P23456
• export_for_pymoluniprotId (required), includeConfidence (optional)

  Export structure data formatted for PyMOL visualization

  Try:Export P04637 structure for PyMOL with confidence coloringTry:Prepare P53350 for visualization in PyMOL
• list_by_organismorganism (required), size (optional)

  List all available structures for a specific organism

  Try:List all structures from Escherichia coliTry:Get available human protein structures
• get_organism_statsorganism (required)

  Get statistics about AlphaFold coverage for an organism

  Try:Get coverage statistics for Homo sapiensTry:Show AlphaFold stats for Arabidopsis thaliana
• find_similar_structuresuniprotId (required), organism (optional)

  Find AlphaFold structures similar to a given protein

  Try:Find structures similar to P04637Try:Show proteins with similar structure to Q8N726 from E. coli
• get_prediction_metadatauniprotId (required)

  Get metadata about the prediction including version, date, and quality metrics

  Try:Get metadata for protein P04637 predictionTry:Show quality metrics for Q8N726

Comparable tools

Installation

# Clone or create the server directory
npm install

# Build the server
npm run build

{
  "mcpServers": {
    "alphafold-server": {
      "command": "node",
      "args": ["/path/to/alphafold-server/build/index.js"]
    }
  }
}

FAQ

What file formats are supported for structure downloads?

The server supports PDB, CIF, BCIF, and JSON formats for structure retrieval and downloads.

How can I handle large batch requests?

The server automatically chunks large requests and includes built-in delays to prevent API overload while processing batch operations.

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