Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ESMfold MCP ServerExtract ESM-2 embeddings for the sequences in proteins.fasta."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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:latestNote: 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:latestNote: 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 outputIn 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 missingGPU 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-codeLicense
Based on Meta AI Research (ESMFold/ESM-2)
This server cannot be installed
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.