Quick Start
Table of contents
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 |