AlphaFold2 MCP Server

Protein structure prediction for monomers, multimers, and batch processing via Docker

An MCP (Model Context Protocol) server for AlphaFold2 protein structure prediction with 5 core tools:

• Predict 3D structure of single proteins (monomers)
• Predict protein complexes (multimers)
• Batch process multiple proteins
• Submit long-running jobs and track their progress
• Analyze FASTA files and get recommendations

Quick Start with Docker

Approach 1: Pull Pre-built Image from GitHub

The fastest way to get started. A pre-built Docker image is automatically published to GitHub Container Registry on every release.

# Pull the latest image
docker pull ghcr.io/macromnex/alphafold2_mcp:latest

# Register with Claude Code (runs as current user to avoid permission issues)
claude mcp add alphafold2 -- docker run -i --rm --user `id -u`:`id -g` --gpus all --ipc=host -v `pwd`:`pwd` ghcr.io/macromnex/alphafold2_mcp:latest

Note: Run from your project directory. `pwd` expands to the current working directory.

Requirements:

• Docker with GPU support (nvidia-docker or Docker with NVIDIA runtime)
• Claude Code installed

That's it! The AlphaFold2 MCP server is now available in Claude Code.

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Approach 2: Build Docker Image Locally

Build the image yourself and install it into Claude Code. Useful for customization or offline environments.

# Clone the repository
git clone https://github.com/MacromNex/alphafold2_mcp.git
cd alphafold2_mcp

# Build the Docker image
docker build -t alphafold2_mcp:latest .

# Register with Claude Code (runs as current user to avoid permission issues)
claude mcp add alphafold2 -- docker run -i --rm --user `id -u`:`id -g` --gpus all --ipc=host -v `pwd`:`pwd` alphafold2_mcp:latest

Note: Run from your project directory. `pwd` expands to the current working directory.

Requirements:

• Docker with GPU support
• Claude Code installed
• Git (to clone the repository)

About the Docker Flags:

• -i — Interactive mode for Claude Code
• --rm — Automatically remove container after exit
• --user `id -u`:`id -g` — Runs the container as your current user, so output files are owned by you (not root)
• --gpus all — Grants access to all available GPUs
• --ipc=host — Uses host IPC namespace for better performance
• -v — Mounts your project directory so the container can access your data

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Verify Installation

After adding the MCP server, you can verify it's working:

# List registered MCP servers
claude mcp list

# You should see 'alphafold2' in the output

In Claude Code, you can now use all 5 AlphaFold2 tools:

• submit_monomer_prediction
• submit_multimer_prediction
• submit_batch_prediction
• get_job_status
• get_job_result

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Next Steps

• Detailed documentation: See detail.md for comprehensive guides on:
  • Available MCP tools and parameters
  • Local Python environment setup (alternative to Docker)
  • Example workflows and use cases
  • Configuration file options
  • AlphaFold database setup

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Usage Examples

Once registered, you can use the AlphaFold2 tools directly in Claude Code. Here are some common workflows:

Example 1: Monomer Structure Prediction

I have a protein sequence in /path/to/protein.fasta. Can you submit a monomer structure prediction using submit_monomer_prediction with the reduced_dbs preset and save results to /path/to/results/?

Example 2: Protein Complex Prediction

I have two protein chains in /path/to/complex.fasta that I want to model as a heterodimer. Can you use submit_multimer_prediction to predict the complex structure and generate 5 prediction attempts?

Example 3: Batch Processing

I have a directory of FASTA files at /path/to/sequences/ containing 10 proteins. Can you submit them for batch prediction using submit_batch_prediction and track the job status until they complete?

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Troubleshooting

Docker not found?

docker --version  # Install Docker if missing

GPU not accessible?

• Ensure NVIDIA Docker runtime is installed
• Check with docker run --gpus all ubuntu nvidia-smi

Claude Code not found?

# Install Claude Code
npm install -g @anthropic-ai/claude-code

AlphaFold databases missing?

• Download from the official AlphaFold database repository
• Use reduced_dbs preset for faster testing without full databases

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License

Based on DeepMind AlphaFold — Apache 2.0