ESMfold MCP Server
Enables protein sequence analysis and structure prediction by extracting ESM-2 embeddings and batch processing FASTA files via Docker. It provides tools for large-scale embedding extraction, job monitoring, and model management within an MCP-compatible environment.
README
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-dockeror 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
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_embeddingssubmit_protein_embeddingssubmit_batch_protein_embeddingsget_job_statusget_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)
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