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maintenanceModel Context Protocol server for protein binder design using BindCraft via Docker, enabling structure prediction, sequence optimization, and scoring.
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"author:MacromNex" matching MCP servers:
- FlicenseNot gradedqualityCmaintenanceEnables RNA structure analysis, sequence evaluation, and inverse design using geometric deep learning models. Supports both quick computational analysis and long-running batch processing for generating RNA sequences that fold into target structures.
- FlicenseNot gradedqualityDmaintenanceEnables protein stability prediction ($DeltaDelta$G and $Delta$Tm) and systematic mutation analysis using the SPIRED-Stab deep learning model. It supports single variant analysis, batch processing, and job monitoring via Docker-based inference.
- FlicenseNot gradedqualityDmaintenanceEnables protein modeling and design using the Rosetta suite via Docker, including structure refinement, mutation stability analysis, docking, and loop modeling through natural language commands.
- FlicenseNot gradedqualityDmaintenanceEnables AI-powered protein design, including binders, peptides, and custom proteins, with GPU-accelerated Docker deployment and async job management.2
- FlicenseNot gradedqualityDmaintenanceEnables 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.
- FlicenseNot gradedqualityDmaintenanceEnables protein structure prediction using the Chai-1 model via Docker, with tools for small peptides, FASTA-based predictions, MSA-enhanced predictions, batch processing, and job management.
- FlicenseNot gradedqualityDmaintenanceEnables AI-powered protein structure prediction and variant analysis via Docker, with tools for submitting predictions, batch processing variants, and monitoring jobs.1