"Exploring Supabase Features and Services" matching MCP servers:

Provides access to EMBL-EBI bioinformatics data including InterPro domains, Pfam families, protein features, and taxonomy through a unified tool.

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.

A production-ready Model Context Protocol (MCP) server that provides comprehensive access to the BioOntology API for searching, annotating, and exploring over 1,200 biological ontologies.

MCP server for interacting with Galaxy bioinformatics platform, enabling AI assistants to connect to Galaxy instances, search and execute tools, manage workflows, and access other features.

Enables molecular generation, optimization, and analysis through NVIDIA MolMIM API. Supports generating drug-like molecules with desired properties, extracting molecular embeddings, and exploring chemical space around seed molecules.

Enables querying NCI Thesaurus and other cancer-research vocabularies served by NCI Enterprise Vocabulary Services, providing codes, synonyms, definitions, and hierarchical relationships via MCP tools.

Enables querying and retrieving bacterial and viral genomic data, features, antimicrobial resistance, and epitopes from the BV-BRC API using natural language.

Enables search and retrieval of academic papers from PubMed database with advanced features like MeSH term lookup, publication statistics, and PICO-based evidence search.

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.

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.

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).

Enables DNA sequence analysis and variant effect prediction using Evo2-7B via MCP tools, providing forward inference, likelihood scoring, and batch variant comparison through natural language.

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 coding agents to interact with the Reactome pathway database, including search, lookup, hierarchy traversal, SBML/SBGN export, and gene-set enrichment analysis.

Provides direct SQL access to a locally hosted Reactome database, enabling schema discovery, guarded read-only queries, and ergonomic helpers over the full relational schema.

Phylogenetic inference server driving IQ-TREE 2, always returning per-clade bootstrap support plus model selection, tree comparison, and alignment simulation, with detailed diagnostics like conflicting clades and model uncertainty.

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.