"Resources or guides related to documentation" matching MCP servers:

Guides researchers, including those new to BPP, from raw sequence data to a validated control file that has passed a short test run. Wraps BPP command-line tools without running long analyses itself.

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.

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 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 assistants to search and retrieve prokaryotic names, taxon details, full classifications, and rank-based browsing from the List of Prokaryotic names with Standing in Nomenclature in real time, plus read related information pages.

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.

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.

A public, read-only MCP server and REST API that connects AI agents to Bioconductor package build, check and propagation state, release and download data, dependency and ops activity, plus searchable infrastructure documentation. Every answer is linked to the public upstream source it came from, with results trimmed to the relevant failing sections or capped lists.

Executes SPARQL queries against biological and biomedical RDF databases from the RDF Portal, with additional REST API integrations for bioinformatics resources.

A unified MCP server for biomedical research that connects AI systems to resources like Ensembl, EuropePMC, STRING, and more, enabling retrieval of verified domain-specific information.

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.

Enables AI assistants to search ImmPort immunology studies and subjects, read study data and assay results, look up controlled vocabularies and the data model, and find study files. Supports study comparison, release history lookups, and guided workflows for cross-study analysis.

Enables generation of chemical structures, reactions, spectra, titration curves, 3D models, and more from natural language or SMILES, using RDKit for offline rendering and supporting formats like PNG, SVG, CDXML, and Anki decks.

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 AI agents to retrieve cited pharmacogenomic and gene-variant information, including drug–gene guidance from CPIC/DPWG and rsID lookups, so responses can quote curated sources instead of relying on memory. A local package also lets users read raw DNA files on their own computer without sending the file data to the remote service.

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.

An MCP server that provides mouse genetics data from Mouse Genome Informatics (MGI), enabling LLM agents to query markers, mutations, alleles, phenotypes, and disease models.

MCP server that exposes the UniProt REST API to LLM clients, enabling search and retrieval of protein data via tools like search_uniprotkb, get_entry, and map_ids.

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 MCP clients to annotate and classify single human genetic variants in any notation, returning an auditable points-based ACMG verdict with its criteria, gnomAD frequencies, in-silico predictors, ClinVar data, and per-transcript consequences. It is read-only, requires no account or API key, and keeps answers compact while linking back to the source.

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.