Genomics MCP
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- AlicenseNot gradedqualityCmaintenanceEnables querying UCSC Genome Browser assemblies, annotation tracks, track data over genomic intervals, and raw DNA sequences across ~250 species without authentication.14 npmMIT
- AlicenseNot gradedqualityCmaintenanceEnables searching cancer genes and curated variants from CIViC, retrieving associated diseases, therapies, and graded evidence items and assertions for clinical interpretation.17 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables researchers to query DigitalBrain data catalogs, brain region profiles, gene expression summaries, and paper evidence, and download approved results through MCP-compatible clients.MIT

mentu-navigator-mcpofficial
AlicenseNot gradedqualityCmaintenanceProvides read-only, provenance-first repository navigation for agents and humans, with ranked lexical retrieval, exact query, document handles, symbol context, and change impact analysis.48 npmApache 2.0- AlicenseAqualityAmaintenanceEnables genealogical research against FamilySearch through read-only tools, resolving historical places as they existed at a given date, searching indexed records and collections, fetching the page images behind them, and reading the community-edited shared tree as leads rather than sources. It works anonymously for the gazetteer and catalogue, and uses your own registered application's access token for records, images, and tree access.281,463 PyPIMIT
- AlicenseNot gradedqualityBmaintenanceEnables querying the gnomAD genome aggregation database for variant, gene, and region information.21 npmMIT
TDQS
Scored across 23 tools
Each tool targets a distinct data type or action: sequence, features, signal, reads, coverage, pileup, variants, samples, metadata, transfers, locus inspection, sample comparison, identifier resolution, variant normalization, variant/gene/protein lookups, source listing, dataset search/description, and file listing. Overlaps like get_reads/get_coverage/get_pileup are differentiated by output, and resolve_identifier vs lookup_* by scope.
All tool names follow a consistent snake_case verb_noun pattern (e.g., get_sequence, list_samples, fetch_file, normalize_variant, lookup_protein). No mixing of conventions or vague verbs; the pattern is predictable across all 23 tools.
23 tools is slightly above the ideal 3-15 range but reasonable given the breadth of genomics data formats (FASTA, BED, GFF, bigWig, BAM, CRAM, VCF) and operations (access, lookup, transfer, inspection). Each tool appears to earn its place, though some consolidation of similar BAM/CRAM tools could reduce count.
The surface covers core genomics workflows: sequences, features, signal, reads, coverage, pileup, variants, samples, datasets, files, transfers, identifier resolution, variant normalization, and lookups for variants/genes/proteins. Minor gaps exist, such as searching genes by keyword or listing variants by gene without a locus, but agents can work around these.