"A service for finding maps and navigation solutions by Amap (Gaode Ditu)" matching MCP servers:

Enables AI clients to connect to Galaxy instances, inspect histories and reports, discover tools and workflows, submit analyses, and monitor their results via interactive cards.

Provides protein family, domain, and functional annotation using InterProScan, supporting local or API backends.

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 variant annotation and effect prediction using the Ensembl VEP API, with support for batch and single queries.

This server enables multi-agent conversations for interacting with Cirro's biological data platform through its OpenAPI interface, auto-generated using AG2's MCP builder.

MCP server offering verified bioinformatics tools for sequence utilities and statistics, backed by BioPython/scipy. Enables AI agents to perform accurate GC content, translation, ORF finding, motif scanning, and statistical tests through natural language.

Enables querying of per-residue missense tolerance, Pfam domain annotations, and variant counts for human transcripts by wrapping the MetaDome web service. Provides MCP tools for resolving transcripts, requesting tolerance landscapes, and identifying constrained regions.

Enables querying and browsing ontologies from the EBI Ontology Lookup Service, including searching for terms, retrieving term details, and navigating ontology hierarchies via natural language.

Enables AI assistants to create, monitor, and manage computational tasks through GA4GH Task Execution Service (TES) functionality. Provides seamless access to TES-compliant services for executing bioinformatics and scientific computing workflows.

Enables users to search and retrieve 3D cryo-EM and electron-tomography density maps by keyword or entry ID, returning details such as resolution, structure-determination method, sample, and release date.

Enables looking up genes, fetching sequences, predicting variant consequences, finding orthologs, and cross-database xrefs via Ensembl REST API through MCP.

Enables searching cryo-EM density maps in EMDB and raw datasets in EMPIAR, with filtering by resolution, keyword, and cross-referencing between the two databases.

Enables querying BindingDB for measured protein/small-molecule binding affinities, including finding ligands that bind a protein, protein targets for a compound, and affinities from PDB structures.

Enables AI agents to search roughly 150 million digitized natural-history museum specimen records (plants, animals, fossils) from US collections, filtered by taxonomy and locality, and to retrieve the full normalized record for any single specimen by its uuid. It also returns taxonomic or geographic specimen counts grouped by a chosen field, optionally narrowed by the same filters, with no API key required.

Enables searching EBI BioStudies, a keyless database of biological study descriptions, by keyword and retrieving full metadata for a single study by accession, including title, abstract, release date, and link counts. Results tie studies across EBI archives such as ArrayExpress and PRIDE, so agents can locate and inspect study records without authentication.

Wraps NCBI BLAST+ blastp into a FastMCP service for auditable protein homology searches with local output artifacts and structured metadata.

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.