"Collaborative Communication Between AI Systems" matching MCP servers:

Enables AI agents to conversationally interact with genomics research networks for data analysis and discovery across multiple Omics AI Explorer platforms. It provides tools for exploring data collections, examining table schemas, and executing SQL queries against datasets like Viral AI and Neuroscience AI.

An MCP server that provides standardized access to biomedical knowledge bases and resources, enabling AI systems to retrieve verified information from sources like bioRxiv, EuropePMC, and various protein/gene databases.

A Model Context Protocol server that interfaces with Biomart databases, allowing models to discover biological datasets, explore attributes/filters, retrieve biological data, and translate between different biological identifiers.

An MCP server for searching and accessing RNA sequencing datasets from the European Nucleotide Archive (ENA), supporting bulk, single-cell, and spatial transcriptomics with advanced filtering and download capabilities.

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.

Integrates the miEAA 3.x bioinformatics platform with Claude Desktop, enabling microRNA enrichment analysis, identifier conversion between miRBase versions, and miRNA-precursor transformations through natural language.

Natural language-driven spatial transcriptomics analysis via MCP. Integrates 60+ methods for preprocessing, visualization, spatial statistics, cell communication, deconvolution, and trajectory analysis.

Allows to retrieve information about an AnnData object via MCP using the read_lazy function from anndata.

A collaborative BrAPI v2.1 workspace for multi-agent research via MCP, enabling search and retrieval of studies, germplasm, genotypes, and more across any BrAPI v2-compliant server.

Enables AI assistants to explore VEuPathDB WDK catalogs, searches, parameters, and gene data, and to perform gene lookups, expression summaries, step estimates, and download URL retrieval using VEuPathDB credentials.

Provides chemical informatics endpoints for converting between chemical names and SMILES, processing molecule structures, and comparing molecules, with MCP compatibility.

Enables searching cryo-EM density maps in EMDB and raw datasets in EMPIAR, with filtering by resolution, keyword, and cross-referencing between the two databases.

A unified MCP server for biomedical research that connects AI systems to resources like Ensembl, EuropePMC, STRING, and more, enabling retrieval of verified domain-specific information.

Enables natural language interface for single-cell RNA-Seq analysis using Liana. Supports reading/writing scRNA-Seq data, cell-cell communication analysis, and visualization through circle plots and dotplots.

🔍 Enable AI assistants to search and access bioRxiv papers through a simple MCP interface. The bioRxiv MCP Server provides a bridge between AI assistants and bioRxiv's preprint repository through the Model Context Protocol (MCP). It allows AI models to search for biology preprints and access their

Enables AI assistants to clean PDB structures and run initial-stage energy relaxation for biomolecular modeling. It provides a structured workflow for preparing structures before production molecular dynamics or coarse-graining pipelines.

Provides read-only access to the ProPaths verified protein interactome, letting AI agents search proteins, retrieve mechanistic interaction details, and explore pathway ontology through MCP tools, resources, and prompts.

Enables AI-assisted molecular biology experiment design with tools for qPCR primer design, cloning strategy optimization, TaqMan probe design, and multiplex compatibility analysis.

Enables AI assistants to run reproducible bioinformatics pipelines over MCP, with verifiable provenance via checksums and Workflow Run RO-Crate metadata.

Enables AI assistants to rapidly gather and synthesize structural, chemical, conservation, and literature data about protein binding pockets for drug-target triage. Useful as a reconnaissance step before computational binder design.