"Local AI Agent Toolkit" matching MCP servers:

MCP server and Claude Plugin for a full ENCODE Project genomic data and analysis toolkit — search, download, track, and analyze functional genomics experiments

Provides local DNA/RNA sequence analysis tools (composition, reverse complement, translation, ORF enumeration, motif scanning) via MCP for agent workflows.

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 compiling typed decision queries into the smallest decision-sufficient evidence context with machine-checkable Context Certificates, providing auditable executable-biology inference through local MCP tools.

Enables AI agents to read and manipulate networks, tables, visual styles, and more in a live Cytoscape Web session through natural language, by connecting over Chrome DevTools Protocol.

Unified genomic track, peak, and sequence retrieval tool for ENCODE, ChIP-Atlas, ReMap, GEO, and SRA/ENA with unified metadata, resolved DOI/PMID provenance, and direct FASTQ download without SRA toolkit.

Enables installing, configuring, and running modular MCP servers for biology, bioinformatics, and bioimaging tasks, including local image analysis, ImageJ/Fiji bridging, and LLM-based agent workflows.

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.

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.

Enables prediction of blood-brain barrier permeability for drug molecules via machine learning, with molecule name lookup, plain-language explanations, similar drug search, and applicability domain checks. Exposes these as MCP tools and orchestrates them via a LangGraph agent.

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.

Enables genomic sequence analysis through the Evo 2 model, supporting DNA sequence scoring, embedding, generation, and variant effect prediction with multiple model checkpoints (7B, 40B, 1B parameters).

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.

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.

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

MCP server that provides tools for querying the Human Phenotype Ontology (HPO) including term lookup, hierarchy exploration, cross-ontology mappings, and gene-phenotype-disease associations, all grounded in a local SQLite database for fast offline lookups.

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

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.

Enables LLM agents to search biomedical literature, retrieve article details, find related papers, manage caching, and download open-access full texts through MCP with structured, agent-friendly responses.

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.