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"Using a second LLM to collaborate with a primary LLM for problem-solving and quality improvement" matching MCP servers:

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    Enables analysis of bulk RNA-seq data using natural language queries, executing R and Python in a Docker container with automatic sample anonymization and privacy controls.
    7
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    An MCP server that provides mouse genetics data from Mouse Genome Informatics (MGI), enabling LLM agents to query markers, mutations, alleles, phenotypes, and disease models.
    13
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    MIT
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    MCP server that exposes the UniProt REST API to LLM clients, enabling search and retrieval of protein data via tools like search_uniprotkb, get_entry, and map_ids.
    7
    MIT
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    MCP server for polygenic risk score analysis, wrapping just-prs to enable catalog search, PRS computation, VCF normalization, percentile and risk estimation, and quality assessment.
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    MIT
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    Converts messy metabolite names into standard database identifiers (KEGG, HMDB, ChEBI, PubChem, InChIKey) and performs crosswalking to Mouse-GEM for metabolic model input, with deterministic tools and an LLM reasoning layer for identity disambiguation.
    20
    MIT
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    Enables LLM agents to query the CZ CELLxGENE Census single-cell atlas with ontology-aware filters, cost caps, and full provenance, allowing natural language questions about cell types, tissues, and gene expression.
    13
    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.
    MIT
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    Provides a natural language interface for scRNA-Seq analysis using the Scanpy library, supporting operations such as data preprocessing, clustering, and visualization. It enables AI agents and clients to perform complex single-cell transcriptomics workflows through the Model Context Protocol.
    2
    BSD 3-Clause
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    Enables AI assistants to generate publication-quality bioinformatics visualizations (volcano plots, PCA, heatmaps, etc.) directly from raw biological data.
    MIT
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    A Model Context Protocol server that enables AI assistants to interact with LAMMPS for molecular dynamics simulations through natural language commands.
    14
    Apache 2.0
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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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    MCP server for biological protein design, folding, and affinity prediction using Refua tools, with optional support for ADMET, clinical simulation, preclinical planning, wet-lab automation, and more.
    MIT