"Speaking to Claude AI via Slack" matching MCP servers:

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.

Allows to retrieve information about an AnnData object via MCP using the read_lazy function from anndata.

Enables AI agents to resolve scientific names to Taxonomic Serial Numbers, traverse complete taxonomic lineages from kingdom to children, and retrieve vernacular names in all languages from an authoritative US-government taxonomy.

Enables AI agents to search public cancer genomics studies (TCGA, CPTAC, MSK, and more), fetch full details for individual studies, resolve gene symbols to Entrez ids, and list cancer types. Works keylessly against open cBioPortal data over a hosted MCP endpoint, a local stdio server, or plain HTTP.

Enables AI agents to search and retrieve compounds, drugs, diseases, pathways, genes, enzymes, glycans, modules, and KO entries; fetch full parsed flat-file entries by ID; and list database contents through keyless REST tools.

MCP server for querying the GWAS Catalog (EBI/NHGRI), a curated catalog of genome-wide association studies. It enables AI agents to search and retrieve study data via natural language or direct tool calls.

MCP server for querying gene annotations, full-text gene search, and species taxonomy via MyGene.info. Enables AI agents to access gene data through natural language questions.

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 keyless lookup of marine species and genus names, retrieval of full taxonomic lineages by AphiaID, and common vernacular names across languages via MCP tools.

Enables AI agents to query the WikiPathways open community pathway database via natural language, part of the Pipeworx MCP gateway.

Enables AI agents to resolve scientific (Latin binomial) names to Open Tree of Life taxon IDs, retrieve full taxonomic details, synonyms, and ancestor lineages, and find the most recent common ancestor of up to 10 taxa within the synthetic tree of life. Runs keylessly over a hosted gateway endpoint or locally via npx.

Provides access to EBI's MetaboLights metabolomics study repository via an MCP gateway, enabling querying and retrieval of metabolomics data.

Reproduces the in-silico toxicological profile of Heracleum sosnowskyi metabolites from Rassabina & Fedorov (2025) using open-source models for LD50 prediction, toxicity classification, chemical space clustering, and synthesis cost estimation.

Enables AI assistants to query VCF files through MCP tools that summarize variants, identify pathogenic and carrier variants, interpret pharmacogenomic results, and determine APOE status, with web app and Claude Desktop support.

BioOpenMCP enables users to run bioinformatics tools like FastQC, Cutadapt, and STAR with background execution and status checking. It integrates with Claude Desktop to perform quality control, trimming, alignment, and reporting via natural language.

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.