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    Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.
    Apache 2.0
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    Provides a collection of MCP servers for computational chemistry tasks including molecular generation and retrosynthesis. Also offers property prediction and molecule pricing capabilities.
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    Parses MS-DIAL binary lipidomics outputs and runs standard analyses server-side, returning compact summaries so an LLM can drive full lipidomics analysis without exposing raw matrices.
    MIT
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    Enables deep probabilistic analysis of single-cell omics data using scvi-tools through natural language. Supports SCVI for scRNA-seq analysis, SCANVI for cell type annotation, TOTALVI for multi-modal RNA/protein data, and PEAKVI for scATAC-seq analysis.
    MIT
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    A specialized MCP server for Metal-Organic Framework research that provides tools for database searching, structural optimization, and energy calculations via ASE. It enables scientific workflows by allowing users to interact with MOF data and perform chemical simulations through a standard SSE interface.
    MIT
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    Natural language-driven spatial transcriptomics analysis via MCP. Integrates 60+ methods for preprocessing, visualization, spatial statistics, cell communication, deconvolution, and trajectory analysis.
    20
    103 PyPI
    44
    MIT
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    Enables running GROMACS molecular dynamics simulations through natural language, with tools for topology building, solvation, simulation management, and trajectory processing via the Model Context Protocol.
    31
    2
    MIT
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    An MCP server that enables single-cell RNA sequencing analysis through natural language, supporting data processing, visualization, and analysis tasks without requiring coding knowledge.
    52
    12
    BSD 3-Clause
  • A
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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.
    MIT
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    Provides chemical informatics endpoints for converting between chemical names and SMILES, processing molecule structures, and comparing molecules, with MCP compatibility.
    5
    MIT
  • F
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    Provides access to the AlphaFold Protein Structure Database with tools for structure retrieval, confidence analysis, batch processing, and visualization.
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    Enables 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.
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    Enables 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.
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  • F
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    Enables AI-powered protein structure prediction and variant analysis via Docker, with tools for submitting predictions, batch processing variants, and monitoring jobs.
    1
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