ESMfold MCP Server

Protein structure prediction using ESMFold via Docker

An MCP (Model Context Protocol) server for ESMFold protein analysis with 5 core tools:

• Extract ESM-2 protein embeddings from sequences or FASTA files

• Submit large-scale embedding extraction jobs

• Batch process multiple FASTA files simultaneously

• Monitor and retrieve background job results

• Access server information and available models

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/esmfold_mcp:latest

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

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

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

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

• extract_protein_embeddings

• submit_protein_embeddings

• submit_batch_protein_embeddings

• 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)

  • ESM-2 model selection guide

  • Example workflows and use cases

  • Output format options (NPZ, JSON)

Usage Examples

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

Example 1: Extract Embeddings from FASTA

I have protein sequences in /path/to/proteins.fasta. Can you extract ESM-2 embeddings using extract_protein_embeddings with the esm2_t33_650M_UR50D model and save the embeddings to /path/to/embeddings/?

Example 2: Large-Scale Embedding Extraction

I have a large dataset of 500 protein sequences in /path/to/large_dataset.fasta. Can you submit a batch embedding extraction job using submit_protein_embeddings with the esm2_t36_3B_UR50D model, then monitor the job until completion and retrieve the results?

Example 3: Mutation Embedding Analysis

I have variant sequences in /path/to/variants.fasta for a mutational study. Can you extract embeddings for all variants using extract_protein_embeddings and save to /path/to/variant_embeddings/ so I can compare them?

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

License

Based on Meta AI Research (ESMFold/ESM-2)