Paleobiology MCP Server
Search fossil occurrences, taxon ranges, diversity through deep time, and the geologic time scale.
Connect it
Settings → Connectors → Add custom connector
URL: https://paleobiology.caseyjhand.com/mcpSettings → Apps & Connectors → Advanced → Developer mode
Create connector with URL: https://paleobiology.caseyjhand.com/mcp{
"mcpServers": {
"paleobiology-mcp-server": {
"url": "https://paleobiology.caseyjhand.com/mcp"
}
}
}claude mcp add --transport http paleobiology-mcp-server https://paleobiology.caseyjhand.com/mcp{
"servers": {
"paleobiology-mcp-server": {
"type": "http",
"url": "https://paleobiology.caseyjhand.com/mcp"
}
}
}{
"mcpServers": {
"paleobiology-mcp-server": {
"command": "npx",
"args": [
"-y",
"@cyanheads/paleobiology-mcp-server@0.4.0"
]
}
}
}claude mcp add paleobiology-mcp-server -- npx -y @cyanheads/paleobiology-mcp-server@0.4.08 tools, verified live
paleobiology_search_occurrencesread-onlySearch fossil occurrences filtered by taxon, geologic time, geography, and depositional environment â the flagship. Use base_name for a clade and all its descendants (what "Tyrannosaurus occurrences" usually means), base_id for that same clade by resolved taxon id, or taxon_name for an exact taxon. Bound the age by a named interval (e.g. "Maastrichtian") or a max_ma/min_ma range, and/or a lng/la
paleobiology_get_taxonread-onlyResolve a taxon by name (e.g. "Tyrannosaurus") or by integer taxon_no to its accepted name, rank, higher classification, immediate parent, fossil occurrence count, and first/last appearance (FAD/LAD) range in millions of years â "when did this clade exist, and what is it." Run this first to resolve a name into the accepted name and taxon_no, then pass that id as base_id to paleobiology_search_oc
paleobiology_get_diversityread-onlyCompute a diversity / origination / extinction curve for a clade across geologic time, binned by period, epoch, or age â answers "plot dinosaur genus diversity across the Mesozoic." Pass a clade-inclusive base_name (or base_id, the same clade by resolved taxon id â exactly one of the two) and bound the span by a named interval (e.g. "Mesozoic") or a max_ma/min_ma range; choose what to count (g
paleobiology_list_intervalsread-onlyLook up the geologic time scale â eons, eras, periods, epochs, and ages with their absolute-age boundaries in millions of years (Ma) and nesting. This is the reference that grounds every temporal filter on the other tools and translates a named interval like "Late Cretaceous" to its 100.5â66.0 Ma boundaries (and back). Filter by a name substring, a Ma range (overlap match), and/or a level; cal
paleobiology_search_collectionsread-onlyFind fossil collections (localities) by area and geologic time â "what has been dug up here, and from what rock." Each locality returns its location, age (named interval and Ma), formation and strata, lithology, depositional environment, and the count of co-occurring fossils. Filter by a clade-inclusive base_name (or base_id, the same clade by resolved taxon id), a named interval or max_ma/min_m
paleobiology_get_referencesread-onlyResolve PBDB reference_no values â the source publication on every paleobiology_search_occurrences and paleobiology_search_collections row â to full citations with authors, year, title, publication, volume, pages, and DOI. Pass the ids from a page of rows in one call: the first 25 distinct ids are resolved and any beyond that come back in remaining_reference_nos for a follow-up call. Ids PBDB
paleobiology_dataframe_queryread-onlyRun a read-only SQL SELECT against occurrence result sets staged on a DataCanvas by paleobiology_search_occurrences. This is how you analyze a large fossil set without re-fetching it: count occurrences by early_interval, group by formation, country (cc), or accepted_name, or filter by a paleo/modern coordinate range. The classification column is JSON â roll up by rank with json_extract_string(cl
paleobiology_dataframe_describeread-onlyList the tables and their columns staged on a DataCanvas by paleobiology_search_occurrences. Call this before paleobiology_dataframe_query to discover the exact table_name and column names to reference in SQL.
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