ProteinMCP: An Agentic AI Framework for Autonomous Protein Engineering

Documentation | Installation | Quick Start | MCP Catalog | Workflows

Prerequisites

The following tools must be installed on your system:

Tool	Purpose	Install Guide
Python 3.10+	Core runtime	python.org
Conda/Mamba	Environment management	miniforge
Node.js / npm	Claude Code CLI	nodejs.org
Docker (with GPU support)	Containerized MCP servers	docs.docker.com
NVIDIA drivers + nvidia-container-toolkit	GPU access in Docker	NVIDIA Container Toolkit

Verify your setup:

python --version       # >= 3.10
conda --version        # or mamba --version
npm --version
docker --version
nvidia-smi             # GPU available
docker run --rm --gpus all nvidia/cuda:12.1.0-base-ubuntu22.04 nvidia-smi  # GPU in Docker

Installation

Step 1 — Create the Python environment

mamba env create -f environment.yml
mamba activate protein-mcp
pip install -r requirements.txt
pip install -e .

Step 2 — Install Claude Code CLI

npm install -g @anthropic-ai/claude-code

Step 3 — Verify the installation

pmcp avail     # List all available MCPs
pskill avail   # List all available workflow skills
claude --version

Supported MCPs

Please find the 38 supported MCPs in the MCP list.

MCPs come in two runtime types:

Type	MCPs	Install method
Python (local venv)	msa_mcp, alphafold2_mcp, msa_mcp, mmseqs2_mcp, ...	quick_setup.sh creates a local env/ venv
Docker (GPU container)	esm_mcp, prottrans_mcp, plmc_mcp, ev_onehot_mcp, bindcraft_mcp, boltzgen_mcp	Docker image build or pull

Installing MCPs

Recommended: local Docker build (faster than pulling from registry):

# For Docker MCPs — build locally (recommended, avoids slow image pulls)
cd tool-mcps/esm_mcp && docker build -t esm_mcp:latest . && cd ../..
cd tool-mcps/prottrans_mcp && docker build -t prottrans_mcp:latest . && cd ../..
cd tool-mcps/plmc_mcp && docker build -t plmc_mcp:latest . && cd ../..
cd tool-mcps/ev_onehot_mcp && docker build -t ev_onehot_mcp:latest . && cd ../..
cd tool-mcps/bindcraft_mcp && docker build -t bindcraft_mcp:latest . && cd ../..
cd tool-mcps/boltzgen_mcp && docker build -t boltzgen_mcp:latest . && cd ../..

Then register with Claude Code:

# pmcp install detects the local image and skips pulling from registry
pmcp install esm_mcp
pmcp install prottrans_mcp
# ... etc

Alternative: auto-install (pulls from registry if no local image):

pmcp install esm_mcp        # Pulls ghcr.io/macromnex/esm_mcp:latest

For Python MCPs (no Docker needed):

pmcp install msa_mcp         # Runs quick_setup.sh, creates local venv

Verify installed MCPs

pmcp status                  # Shows installed/registered status
claude mcp list              # Health-check all registered MCPs

Quick Start

Option A — Workflow Skills (recommended)

Skills are guided workflows that orchestrate multiple MCP servers via Claude Code.

# Install a workflow (auto-installs all required MCPs)
pskill install fitness_modeling

# Launch Claude Code and run the skill
claude
> /fitness-model

Claude will prompt you for inputs (protein name, data location, etc.) and execute the full pipeline.

Available skills:

Skill	Required MCPs	Description
fitness_modeling	msa_mcp, plmc_mcp, ev_onehot_mcp, esm_mcp, prottrans_mcp	Protein fitness prediction
binder_design	bindcraft_mcp	De novo binder design (RFdiffusion + ProteinMPNN + AF2)
nanobody_design	boltzgen_mcp	Nanobody CDR loop design with BoltzGen

Option B — Jupyter Notebooks

Standalone notebooks for step-by-step exploration. Each notebook installs dependencies, registers MCPs, and walks through the full workflow.

Notebook	Workflow	Description
fitness_modeling.ipynb	Fitness Prediction	MSA, PLMC, EV+OneHot, ESM, ProtTrans, and visualization
binder_design.ipynb	Binder Design	De novo binder design with BindCraft
nanobody_design.ipynb	Nanobody Design	Nanobody CDR loop design with BoltzGen

Usage

MCP management

pmcp avail                # List all available MCPs
pmcp info msa_mcp         # Show MCP details
pmcp install msa_mcp      # Install an MCP
pmcp uninstall msa_mcp    # Uninstall an MCP
pmcp status               # Show installed/registered status

MCP creation

# Create from GitHub repository
pmcp create --github-url https://github.com/jwohlwend/boltz \
  --mcp-dir tool-mcps/boltz_mcp \
  --use-case-filter 'structure prediction with boltz2, affinity prediction with boltz2'

# Create from local directory
pmcp create --local-repo-path tool-mcps/protein_sol_mcp/scripts/protein-sol/ \
  --mcp-dir tool-mcps/protein_sol_mcp

Workflow Skill management

pskill avail              # List available workflow skills
pskill info binder_design # Show workflow details
pskill install binder_design   # Install skill + all required MCPs
pskill uninstall binder_design # Remove skill

Licenses

This software is open-sourced under