About carto-explore-datawarehouse
carto-explore-datawarehouse is a skill for discovering connections, tables, columns, and named sources before querying or building maps. It uses CARTO MCP tools where available, with CLI commands as a fallback for restricted or scripted sessions.
Key features
- 01List and inspect connections
- 02Browse project, dataset, and table hierarchies
- 03Search for resources by text
- 04Inspect table columns and types
- 05Find and inspect named sources
Use cases
- 01Find tables before writing a query
- 02Check column types before authoring SQL
- 03Locate a named source referenced by name
- 04Explore data in a scripted or headless session
MCP support
It primarily uses CARTO MCP tools such as `explore_data` and `manage_named_sources` to inspect connections and resources. CARTO CLI commands provide a fallback when the MCP server is unavailable or the session lacks required scopes.
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ cartodb/ agent-skills --skill carto-explore-datawarehouseAfter installing, type/carto-explore-datawarehousein Claude Code to confirm it loaded.
Bundled filesreferences/connection-browse.mdreferences/named-sources.md
Details
From the project READMEcarto-explore-datawarehouse
Before writing SQL or building maps, an agent usually needs to know what's in the warehouse. This skill covers discovery, matched across MCP and CLI:
| Task | MCP (primary) | CLI (fallback) |
|---|---|---|
| List / inspect connections | explore_data (list_connections, get_connection) | carto connections list / get |
| Walk the hierarchy (project → dataset → table) | explore_data (list_resources) | carto connections browse |
| Full-text find a resource | explore_data (search) | — |
| Columns + types for a table | explore_data (describe) | carto connections describe |
| Find / inspect a named source | manage_named_sources (list, get) | carto named-sources list / get |
Access-path routing.
explore_dataworks on any attached MCP session, but not all its methods do on a token:list_connections,list_resources, andsearchneed only the MCP Server scope, whiledescribeadditionally needs the Maps API on a token session (it's always available over OAuth).manage_named_sourcesis an authoring tool, so it needs an OAuth session (it's hidden on token sessions). Use thecarto connections/carto named-sourcesCLI when the server isn't attached, when a token lacks the scope fordescribe, or when the exploration is scripted/headless. Detection signals and the full routing table:carto-basics/references/access-paths.md.
When to use this skill
- You don't know which tables / schemas exist in a connection.
- You need a column list and types before writing SQL or authoring a map.
- The user references "the named source for X" and you need to find it.
If you already know the table and just want to query it, jump to carto-query-datawarehouse.
Path syntax by engine
The path passed to list_resources / describe (or connections browse / describe) depends on the engine:
| Engine | Path shape |
|---|---|
| BigQuery | project.dataset.table |
| Snowflake | DATABASE.SCHEMA.TABLE |
| Postgres / Redshift | schema.table (no leading project/database) |
| Databricks | catalog.schema.table |
CLI examples:
carto connections browse <name> # top level
carto connections browse <name> "carto-demo-data.demo_tables" # drill in
carto connections describe <name> "carto-demo-data.demo_tables.nyc_collisions"
What's in this skill
| Topic | Reference |
|---|---|
| Browsing and describing a connection in detail | references/connection-browse.md |
| Named sources — what they are, how to list and inspect them | references/named-sources.md |
Always-on guidance
- Browse before you query. A two-second
list_resourcesusually saves a five-minute "table not found" loop. describereturns column types — use them to write correct SQL (e.g. don'tST_DWithinagainst aSTRINGcolumn mistakenly namedgeom).- Paginate long lists — CLI
browsedefaults to--page-size 30; bump it for datasets with hundreds of tables. - Named sources ≠ tables. They're parameterized queries — inspect the underlying tables before assuming a column you see in the source exists in raw form.
carto-demo-datais a public BigQuery dataset CARTO ships — browsing it works on any BigQuery connection with the right IAM, a fast way to validate a fresh connection without touching customer data.