# io.github.cyanheads/paleobiology-mcp-server

> Search fossil occurrences, taxon ranges, diversity through deep time, and the geologic time scale.

- name: io.github.cyanheads/paleobiology-mcp-server
- version: 0.4.0
- connection class: R0 (autonomous)
- trust: 94/100
- quality: 84/100 (good)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/io.github.cyanheads%2Fpaleobiology-mcp-server
- tools: https://api.protogrid.dev/v1/servers/io.github.cyanheads%2Fpaleobiology-mcp-server/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "paleobiology-mcp-server": {
      "type": "http",
      "url": "https://paleobiology.caseyjhand.com/mcp"
    }
  }
}
```


## Trust

- hygiene: 100
- liveness: 100
- freshness: 100
- provenance: 80
- drivers: +repository +namespace-matches-repo +reachable +uptime-99% +updated-5d-ago
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 84/100 (good)

### protocol: 88 (weight 25)

- pass `protocol.modern`: supports 2026-07-28 (server/discover)
- pass `protocol.stateless`: answers without a session
- pass `protocol.transport`: streamable HTTP
- warn `protocol.list_ttl`: tools/list declares ttlMs 0, so clients re-fetch it on every use

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 79 (weight 30)

- pass `tools.descriptions`: every tool has a description
- warn `tools.description_length`: 1 tools have descriptions over 1,024 characters, which crowds the context
- pass `tools.schemas`: every tool has an object input schema
- pass `tools.annotations`: 8 of 8 tools declare readOnlyHint or destructiveHint
- fail `tools.directory_hints`: no tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: paleobiology_get_references (destructiveHint); paleobiology_search_occurrences (destructiveHint); paleobiology_get_taxon (destructiveHint); …
- pass `tools.token_cost`: about 4,700 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 75 (weight 15)

- warn `stability.changes`: 7 tool changes in 30 days
- pass `stability.rug_pull`: no tool changed its meaning under the same name

### dependencies: 100 (weight 15)

- pass `deps.known_vulns`: no known advisory in 96 resolved packages
- pass `deps.mcp_sdk_version`: @modelcontextprotocol/core 2.3.1, no known advisory
- pass `deps.resolvable`: @cyanheads/paleobiology-mcp-server@0.4.0, @cyanheads/paleobiology-mcp-server@0.4.0 resolved: 96 packages

- tools: 8, about 4,700 tokens to load them all
- tool set hash: 4a32aed6fdb22336546e55216dfe21c5
- tools last changed: 2026-10-15T23:28:26.715Z
- badge: [![protogrid quality](https://protogrid.dev/badge/io.github.cyanheads/paleobiology-mcp-server.svg)](https://protogrid.dev/servers/io.github.cyanheads/paleobiology-mcp-server)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

- 2026-10-15 `paleobiology_dataframe_query` changed (description, inputSchema, outputSchema)
  - before: Run 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 — roll up by rank with json_extract_string(classification, '$.family') (also $.phylum, $.class, $.order, $.genus). Staged rows are occurrences, so collection-only fields such as lithology are not present. Reference tables by the table_name that search_occurrences returned — call paleobiology_dataframe_describe first if you do not know the table or column names. SELECT only; writes and file-reading functions are rejected.
  - after: Run a read-only SQL SELECT against occurrence result sets staged on a DataCanvas by paleobiology_search_occurrences. This is how you analyze a large fossil set without re-fetching it: count occurrences by early_interval, group by formation, country (cc), or accepted_name, or filter by a paleo/modern coordinate range. The classification column is JSON — roll up by rank with json_extract_string(classification, '$.family') (also $.phylum, $.class, $.order, $.genus). Staged rows are occurrences, so collection-only fields such as lithology are not present. Reference tables by the table_name that paleobiology_search_occurrences returned — call paleobiology_dataframe_describe first if you do not know the table or column names. A result too large to return inline comes back as its first rows, with a notice naming the ORDER BY … LIMIT/OFFSET that reads the rest. SELECT only; writes and file-reading functions are rejected.
- 2026-10-15 `paleobiology_get_references` added
  - Resolve PBDB reference_no values — the source publication on every paleobiology_search_occurrences and paleobiology_search_collections row — 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 has no reference for are listed in not_found. Results keep the order the ids were given.
- 2026-10-15 `paleobiology_search_collections` changed (inputSchema, outputSchema)
- 2026-10-15 `paleobiology_list_intervals` changed (inputSchema, outputSchema)
- 2026-10-15 `paleobiology_get_diversity` changed (outputSchema)
- 2026-10-15 `paleobiology_get_taxon` changed (inputSchema, outputSchema)
- 2026-10-15 `paleobiology_search_occurrences` changed (description, inputSchema, outputSchema)
  - before: Search fossil occurrences filtered by taxon, geologic time, geography, and depositional environment — 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/lat bounding box; scope to a single locality with collection_no (take it from a paleobiology_search_collections row). At least one filter is required — taxon, time, place, environment, or collection_no. Every row carries two distinct coordinate systems — modern lng/lat (where the rock is today) and paleo lng/lat (where the landmass sat at deposition) — plus the formation, age interval, and higher classification (phylum through genus); never plot a deep-time occurrence on a modern coastline. Resolve a name with paleobiology_get_taxon first if unsure. Broad queries return many rows: an inline preview answers the immediate question, and when the set outgrows that preview the matching occurrences — up to the per-call cap — stage on a DataCanvas (canvas_id + table_name, returned only then) for SQL via paleobiology_dataframe_query (count by interval, group by formation/country, map by region). The response reports how many occurrences matched in total, which rows this page covers, and the offset that reaches the next page — page through the whole match set with limit/offset.
  - after: Search fossil occurrences filtered by taxon, geologic time, geography, and depositional environment — 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/lat bounding box; scope to a single locality with collection_no (take it from a paleobiology_search_collections row). At least one filter is required — taxon, time, place, environment, or collection_no. Every row carries two distinct coordinate systems — modern lng/lat (where the rock is today) and paleo lng/lat (where the landmass sat at deposition) — plus the formation, age interval, and higher classification (phylum through genus); never plot a deep-time occurrence on a modern coastline. Resolve a name with paleobiology_get_taxon first if unsure. Broad queries return many rows: an inline preview answers the immediate question. When this deployment has DataCanvas enabled, a set that outgrows the inline preview stages on a canvas (canvas_id + table_name, returned only then): list its columns with paleobiology_dataframe_describe, then run SQL with paleobiology_dataframe_query (count by interval, group by formation/country, map by region). The response reports how many occurrences matched in total, which rows this page covers, and the offset that reaches the next page — page through the whole match set with limit/offset.

Full history: https://api.protogrid.dev/v1/servers/io.github.cyanheads%2Fpaleobiology-mcp-server/changes

## Dependencies

- npm @cyanheads/paleobiology-mcp-server@0.4.0: resolved, 47 dependencies, MCP SDK @modelcontextprotocol/core 2.3.1
- npm @cyanheads/paleobiology-mcp-server@0.4.0: resolved, 47 dependencies, MCP SDK @modelcontextprotocol/core 2.3.1

Dependency graphs from deps.dev; advisories from OSV.dev, including the GitHub Advisory Database and the PyPI Advisory Database; all CC BY 4.0.

## Remotes

- https://paleobiology.caseyjhand.com/mcp (streamable-http, auth none, reachable true, uptime30d 0.99159664)

## Packages

- npm @cyanheads/paleobiology-mcp-server@0.4.0
- npm @cyanheads/paleobiology-mcp-server@0.4.0

## Tools (8)

- `paleobiology_dataframe_describe`: List 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.
- `paleobiology_dataframe_query`: Run 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 — roll up by rank with json_extract_string(classification, '$.family') (also $.phylum, $.class, $.order, $.genus). Staged rows are occurrences, so collection-only fields such as lithology are not present. Reference tables by the table_name that paleobiology_search_occurrences returned — call paleobiology_dataframe_describe first if you do not know the table or column names. A result too large to return inline comes back as its first rows, with a notice naming the ORDER BY … LIMIT/OFFSET that reads the rest. SELECT only; writes and file-reading functions are rejected.
- `paleobiology_get_diversity`: Compute a diversity / origination / extinction curve for a clade across geologic time, binned by period, epoch, or age — answers "plot dinosaur genus diversity across the Mesozoic." Pass a clade-inclusive base_name (or base_id, the same clade by resolved taxon id — 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 (genera, species, or families) and the bin resolution. The full bin set returns inline — a diversity series is a bounded set of geologic intervals — so you read the curve, the turnover, and the per-bin origination/extinction directly. Counts reflect SAMPLED diversity, biased by collection effort and rock availability, not true past diversity.
- `paleobiology_get_references`: Resolve PBDB reference_no values — the source publication on every paleobiology_search_occurrences and paleobiology_search_collections row — 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 has no reference for are listed in not_found. Results keep the order the ids were given.
- `paleobiology_get_taxon`: Resolve 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 — "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_occurrences, paleobiology_get_diversity, or paleobiology_search_collections for a clade-inclusive filter that carries no name ambiguity (the same id also appears as accepted_no on occurrence rows). Set show_children to also list immediate child taxa. PBDB taxonomy is opinionated and can differ from GBIF's backbone, so the accepted name may differ from the name you searched.
- `paleobiology_list_intervals`: Look up the geologic time scale — 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 100.5–66.0 Ma boundaries (and back). Filter by a name substring, a Ma range (overlap match), and/or a level; call with no filters to browse the full scale. Browsing and every name on the bundled ICS international-scale snapshot are answered offline. A name the snapshot does not carry — the sub-stage and regional names that occurrence and collection rows report, such as "Late Maastrichtian" or "Lancian" — costs one PBDB lookup across its other time scales; the response names which source answered and which scale the interval belongs to.
- `paleobiology_search_collections`: Find fossil collections (localities) by area and geologic time — "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_ma range, a lng/lat bounding box, a formation or lithology name, and/or an environment. Results page inline via limit/offset (the response discloses when more remain). Take a collection_no from a row and pass it — or the same bbox+interval — to paleobiology_search_occurrences to see the actual fauna found together.
- `paleobiology_search_occurrences`: Search fossil occurrences filtered by taxon, geologic time, geography, and depositional environment — 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/lat bounding box; scope to a single locality with collection_no (take it from a paleobiology_search_collections row). At least one filter is required — taxon, time, place, environment, or collection_no. Every row carries two distinct coordinate systems — modern lng/lat (where the rock is today) and paleo lng/lat (where the landmass sat at deposition) — plus the formation, age interval, and higher classification (phylum through genus); never plot a deep-time occurrence on a modern coastline. Resolve a name with paleobiology_get_taxon first if unsure. Broad queries return many rows: an inline preview answers the immediate question. When this deployment has DataCanvas enabled, a set that outgrows the inline preview stages on a canvas (canvas_id + table_name, returned only then): list its columns with paleobiology_dataframe_describe, then run SQL with paleobiology_dataframe_query (count by interval, group by formation/country, map by region). The response reports how many occurrences matched in total, which rows this page covers, and the offset that reaches the next page — page through the whole match set with limit/offset.