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    An MCP server that enables AI coding assistants to interact with Rosetta, PyRosetta, and Biotite for running RosettaScripts, validating XML, translating between Rosetta and Biotite, scoring structures, and querying documentation.
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    MIT
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    Provides seamless access to the Protein Data Bank in Europe (PDBe) API and search capabilities, enabling AI clients to query protein structures, perform advanced searches, and retrieve structural biology data.
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    Apache 2.0
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    Provides programmatic access to AlphaFold protein structure predictions and UniProt data, enabling users to retrieve protein structures, summaries, and annotations through natural language.
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    A Model Context Protocol server providing programmatic access to 3D protein structural data from RCSB PDB, PDBe, and UniProt, enabling search, retrieval, comparison, and analysis of protein structures.
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    Apache 2.0
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    Provides chemical informatics endpoints for converting between chemical names and SMILES, processing molecule structures, and comparing molecules, with MCP compatibility.
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    MIT
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    Provides access to AlphaFold predicted protein 3D structures from EBI, enabling retrieval of prediction metadata, summaries, annotations, and UniProt data.
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    MIT
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    An MCP server that enables language models to fetch protein information from the UniProt database, including protein details, sequences, functions, and structures.
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    MIT
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    Control PyMOL from Cursor via natural language. Enables describing molecular structures and styles in plain language to execute PyMOL commands through XML-RPC.
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    Enables 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.
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    Enables searching, retrieving, and downloading protein structure data from the RCSB Protein Data Bank. Supports intelligent protein structure search, comprehensive data retrieval, and multiple file format downloads for bioinformatics research.
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    MIT
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    Enables AI assistants to perform quality control analysis on high-throughput sequencing data using FastQC and MultiQC. It supports single-file and batch processing of FASTQ/FASTA files and generates comprehensive, interactive summary reports.
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    MIT
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    Enables Claude Code to interact with a TACC or SLURM HPC cluster for bioinformatics pipelines, allowing job management, log reading, file browsing, remote script execution, and job submission through natural language.
    Last updated