Paleobiology Database MCP. Query Earth's 540 Million Years of Fossil History.

You're connected to the Paleobiology Database, so your AI client turns into a seriously sharp paleontological research machine. This isn't just browsing; you're querying millions of fossil records that track life on Earth from phyla right down to individual finds. You'll use this server to pinpoint specific fossils, map out how life evolved across deep time, or figure out where ancient populations moved.

To find a specific fossil occurrence, you start by listing available records. Run list_occurrences or list_collections and filter down the dataset using location parameters or species names. For deeper dives on one single record, use get_occurrence. If you're tracking physical samples, you can run list_specimens to see individual museum specimens, then pull all associated data points for a specific sample ID using get_specimen, or get a detailed list of measurements attached via list_specimen_measurements.

To map out the scope of life on Earth, you've got tools that define context. You can check available time periods by running list_timescales to see every major geological era used in the database; for specific time divisions, list_intervals gives you a list like 'Cretaceous Period.' If you need to constrain the data by rock type or formation, run list_strata or use get_config to pull core settings that detail all available continents and lithologies (rock types).

When it comes to cataloging life, you're pulling from massive taxonomic resources. Use list_taxa to get a list of names and their parent/child species relationships. You can then run get_taxon for deep details on one specific group—say, Tyrannosaurus—or use the autocomplete functions like autocomplete_taxa as you type your query to ensure accuracy across taxa, strata, or intervals.

Tracking how diverse life was over time is where this thing shines. To get a full computation of every different kind of fossil that existed during specific geological periods, run get_occurrences_diversity. If you need a faster, preliminary look at diversity metrics across time, use get_occurrences_quickdiv. You can also pinpoint the most common types of fossils (taxa) within any selected group using get_occurrences_prevalence.

To understand movement and distribution, you run pattern recognition tools. Execute get_occurrences_geosum to summarize multiple fossil finds into distinct geographic clusters, letting you identify major hotspot areas or trace ancient migration paths. You can also get a general sense of where multiple collections are from by running get_collections_summary, which groups findings into broad geographic zones.

For academic rigor, you've got tools that handle the messy side of paleontology. To pull detailed information on how an academic committee classified a taxon, run get_opinion or get a list of available scholarly opinions via list_opinions. If you need source material details, use list_references to check available bibliographic records, and then run get_reference to pull the specifics for one record.

You can even cross-check if a provided reference matches an existing PBDB entry using match_reference.

Need quick suggestions? If you're typing into any field—whether it's a taxa name, strata, or interval—you don't have to guess; use autocomplete_taxa, autocomplete_strata, and autocomplete_combined for immediate help. The tools give you the power to map out entire family trees using get_occurrences_taxa through related fossil occurrences, or pull detailed data on a single collection by ID with get_collection.

You're not just querying; you're building a complete picture of Earth’s history.