MCP for Boltz-2 model inference
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# boltz-mcp MCP (Model Context Protocol) server for Boltz-2 protein structure prediction model. ## Overview This MCP server provides tools for protein structure prediction using the state-of-the-art Boltz-2 model. It enables you to: - Predict single protein structures from amino acid sequences - Predict protein complexes and multimers - Predict protein-ligand interactions - Use custom multiple sequence alignments (MSAs) - Handle cyclic peptides - Configure various prediction parameters ## Features ### Tools Available 1. **`boltz_predict_structure`** - Main prediction tool with full configuration options 2. **`boltz_predict_from_sequences`** - Simple sequence-to-structure prediction 3. **`boltz_check_status`** - Check Boltz installation status 4. **`boltz_get_examples`** - Get example configurations for different prediction types ### Resources Available - **`resource://boltz-usage-guide`** - Comprehensive usage guide and documentation ## Installation ### Prerequisites #### System Dependencies Before installing the Python packages, you need to install system dependencies required for building scientific Python packages: **Ubuntu/Debian:** ```bash sudo apt update sudo apt install -y cmake build-essential gfortran ``` **CentOS/RHEL/Fedora:** ```bash # For CentOS/RHEL sudo yum install cmake gcc-gfortran gcc-c++ make # For Fedora sudo dnf install cmake gcc-gfortran gcc-c++ make ``` **macOS:** ```bash # Install Xcode Command Line Tools if not already installed xcode-select --install # Install gfortran (via Homebrew) brew install gcc cmake ``` **Note:** These system dependencies are required because some Python packages (like SciPy) need to be compiled from source when using uv, and they require: - `cmake`: For building dm-tree and other native extensions - `gfortran`: For building SciPy from source - `build-essential`/`gcc-c++`: For general C/C++ compilation #### Python Dependencies 1. Install the Boltz-2 model: ```bash pip install boltz ``` 2…
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