"React - JavaScript Library for Building User Interfaces" matching MCP servers:

This server enables multi-agent conversations for interacting with Cirro's biological data platform through its OpenAPI interface, auto-generated using AG2's MCP builder.

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 that interfaces with Gigwa for genotyping data import, analysis, and audit, enabling users to perform complex workflows through natural language commands.

An MCP server that provides tools for searching and fetching protein data from the UniProt database using the unipressed library.

Provides standardized access to aging and longevity research data from the OpenGenes database, enabling AI assistants to query comprehensive biomedical datasets through SQL and structured interfaces.

A Model Context Protocol server that provides tools for interacting with the STRING database to analyze protein-protein interaction networks and functional enrichment. It enables users to map protein identifiers, retrieve interaction data, and generate biological network visualizations through natural language interfaces.

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.

Enables workflow management and Docker image building for Bio-OS platform. Supports WDL workflow submission, validation, and monitoring, along with Docker image building and status tracking for bioinformatics workflows.

Enables read-only exploration of Copick cryo-ET projects and discovery/validation of copick CLI commands for building processing pipelines.

Enables building and analyzing signalling networks from interaction databases through a Model Context Protocol server.

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.

Enables LLM agents to design proteins, predict structures, score interfaces, and run molecular dynamics simulations through a unified interface.

An MCP server for the gget bioinformatics library that enables AI assistants to perform complex genomics queries, including gene sequence retrieval, BLAST alignments, and protein structure predictions.

Enables LLMs and AI agents to search a biomedical knowledge graph for concepts and study variables, traverse semantic relationships, and look up BioData Catalyst PIC-SURE paths for cohort building.

Framework for building bioengineering automation tools that AI assistants can call via the Model Context Protocol, handling server registration and tool discovery automatically.

Enables natural language interaction for scRNA-Seq analysis including preprocessing, clustering, and visualization using the CellRank library. It allows users and agents to perform complex genomic data tasks through standard MCP clients and frameworks.

Manages local protein experiments with a Flask backend and SQLite, offering tools for protein library management, Beer-Lambert concentration calculations, BLI dilution planning, and experiment archiving. It provides 7 MCP tools for AI assistants like Claude to interact with the system.

An MCP server that grounds protein research in the UniProt SPARQL endpoint, providing tools for querying proteins, sequences, variants, diseases, and more via intent-named tools and raw SPARQL.

Enables language models to search biomedical literature, fetch sequences, and follow links across Entrez databases through eleven read-only tools wrapping the nine NCBI Entrez E-utilities. It handles URL building, pacing, redirects, response caps, and API-key redaction so queries can be answered without a browser or scraping.

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.