"API for Framer design tool" matching MCP servers:

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

Provides an MCP interface to the ROBOT command-line tool for OWL ontology editing, enabling operations like merging, reasoning, and conversion via natural language.

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.

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

Enables querying of the Monarch Initiative biomedical knowledge graph for genes, diseases, phenotypes, and their associations through natural language or direct tool calls.

Enables AI agents to query Human Phenotype Ontology clinical phenotype terms, navigate term hierarchies, and retrieve gene-disease and disease-phenotype annotations through keyless MCP tools.

Validates the physical and chemical plausibility of ligand–protein docking poses using the PoseBusters tool.

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 gives LLM agents access to computational protein design tools.

Provides a collection of MCP servers for computational chemistry tasks including molecular generation and retrosynthesis. Also offers property prediction and molecule pricing capabilities.

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.

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

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.

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.

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.

MCP server that provides tools to query harmonized gene-disease validity data from the Gene Curation Coalition, supporting consensus and conflict detection for gene-disease assertions.

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.