"Resources and Assistance for Website Design, Frontend UX Flow, and Backend Design" matching MCP servers:

An MCP server that gives LLM agents access to computational protein design tools.

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

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

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

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.

MCP server exposing REINVENT4 generative molecular-design operations as validated, LLM-callable tools for drug discovery, including sampling, transfer learning, reinforcement learning, and molecular analysis.

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.

Enables molecular design and simulation through 45 chemistry tools including pKa calculations, geometry optimization, conformer searches, docking, protein cofolding, and ADMET predictions powered by Rowan's computational chemistry platform.

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.

An MCP server that enables scRNA-Seq analysis through natural language, providing tools for data preprocessing, clustering, and biological visualization. It supports both predefined function execution and a flexible code mode powered by a Jupyter backend for automated single-cell transcriptomics workflows.

Executes SPARQL queries against biological and biomedical RDF databases from the RDF Portal, with additional REST API integrations for bioinformatics resources.

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.

MCP server for gene family analysis, providing tools for FASTA validation and PlantCARE cis-element prediction, with backend task management for AI agents.

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.

Enables protein modeling and design using the Rosetta suite via Docker, including structure refinement, mutation stability analysis, docking, and loop modeling through natural language commands.

Enables AI-powered protein design, including binders, peptides, and custom proteins, with GPU-accelerated Docker deployment and async job management.

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.

Grounds gene-nomenclature work in the HUGO Gene Nomenclature Committee (HGNC) dataset, enabling resolution of gene symbols and IDs to canonical HGNC identifiers, plus cross-references and batch operations.