"Exploring memories or concepts related to windsurfing" matching MCP servers:

A bridge connecting AI agents to NCBI's PubMed database through the Model Context Protocol, enabling seamless searching, retrieval, and analysis of biomedical literature and data.

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 interaction with MGnify metagenomics resources and tools through the Model Context Protocol. Provides access to MGnify's API for querying and analyzing metagenomic datasets and related biological information.

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.

A Model Context Protocol server that enhances language models with protein structure analysis capabilities, enabling detailed active site analysis and disease-related protein searches through established protein databases.

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.

Federates 13 gene-related MCP backends (gnomAD, GTEx, etc.) behind a single Streamable HTTP endpoint with collision-free namespacing and search-based tool discovery.

Enables AI assistants to query VirtualFlyBrain data, run queries, and search for terms related to Drosophila neurobiology.

Enables LLMs and AI agents to search a biomedical knowledge graph for concepts and study variables, traverse semantic relationships, and look up BioData Catalyst PIC-SURE paths for cohort building.

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 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.

A Model Context Protocol (MCP) server for interacting with Gen3 data commons, with GraphQL query validation to reduce hallucinations.

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.

Empowers AI agents with direct access to the official ClinicalTrials.gov database, enabling programmatic searching, retrieval, and analysis of clinical study data through a Model Context Protocol interface.

A Model Context Protocol server that interfaces with Biomart databases, allowing models to discover biological datasets, explore attributes/filters, retrieve biological data, and translate between different biological identifiers.