AlphaFold3 MCP Server

AI-powered protein structure prediction and variant analysis via Docker

An MCP (Model Context Protocol) server for AlphaFold3 structure prediction with 5 core tools:

• Submit structure predictions from sequences or MSA files

• Batch process protein variants for engineering workflows

• Run end-to-end prepare-and-predict variant pipelines

• Monitor long-running prediction jobs

• Validate and prepare AlphaFold3 input configurations

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/alphafold3_mcp:latest

# Register with Claude Code (runs as current user to avoid permission issues)
claude mcp add alphafold3 -- docker run -i --rm --user `id -u`:`id -g` --gpus all --ipc=host -v `pwd`:`pwd` ghcr.io/macromnex/alphafold3_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 AlphaFold3 MCP server is now available in Claude Code.

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/alphafold3_mcp.git
cd alphafold3_mcp

# Build the Docker image
docker build -t alphafold3_mcp:latest .

# Register with Claude Code (runs as current user to avoid permission issues)
claude mcp add alphafold3 -- docker run -i --rm --user `id -u`:`id -g` --gpus all --ipc=host -v `pwd`:`pwd` alphafold3_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

Related MCP server: SPIRED-Stab MCP

Verify Installation

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

# List registered MCP servers
claude mcp list

# You should see 'alphafold3' in the output

In Claude Code, you can now use all 5 AlphaFold3 tools:

• submit_structure_prediction

• submit_batch_variants

• submit_prepare_and_predict_variants

• get_job_status

• get_job_result

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 formats

  • AlphaFold3 license and model weight setup

Usage Examples

Once registered, you can use the AlphaFold3 tools directly in Claude Code. Here are some common workflows:

Example 1: Structure Prediction from Sequence

I have a protein sequence in /path/to/protein.fasta. Can you submit an AlphaFold3 structure prediction using submit_structure_prediction and save the results to /path/to/results/?

Example 2: Batch Variant Analysis

I have 50 protein variants in /path/to/variants.fasta and a wild-type data JSON at /path/to/wt_data.json. Can you use submit_prepare_and_predict_variants to run end-to-end structure predictions for all variants and save to /path/to/output/?

Example 3: Protein-Ligand Complex

I want to predict the structure of my protein with a small molecule ligand. The protein is in /path/to/protein.fasta and the ligand SMILES is "CCO". Can you prepare the AlphaFold3 config and submit a structure prediction?

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

AlphaFold3 license required?

• AlphaFold3 model weights require a license from Google DeepMind

• Apply at: https://github.com/google-deepmind/alphafold3

License

CC-BY-NC-SA 4.0 (Google DeepMind)