# Tools reference

> Every MCP tool your AI assistant gets from Orcabase, grouped by what it does, plus what’s deliberately left out: no edits, deletes or settings.

Source: https://tini.so/docs/connect-ai/tools

These are the tools Orcabase gives an AI assistant over MCP. The built-in [Data Agent](https://tini.so/docs/agent) uses the same ones, except the two notebook tools, plus one of its own for drawing charts in the chat. Every tool acts on the organization the token belongs to.

## Discover

| Tool | What it does |
| --- | --- |
| `list_data_sources` | Lists the data sources the assistant can query: name, engine (Postgres, BigQuery or DuckDB) and kind. |
| `list_schemas` | Lists the schemas (BigQuery datasets) in a data source. |
| `list_tables` | Lists the tables and views in a schema. |
| `describe_table` | A table’s columns and types, so SQL is written against the real schema instead of guesses. |
| `preview_table` | A handful of sample rows, to see real values, formats and codes. |

## Query

| Tool | What it does |
| --- | --- |
| `run_query` | Runs SQL against a data source and returns the result (up to 5,000 rows). Saves nothing. |
| `list_queries` | Lists saved queries, so existing work is reused rather than rewritten. |
| `run_saved_query` | Re-runs a saved query and saves its new result, which is what dashboards show. |

## Metrics and data models

| Tool | What it does |
| --- | --- |
| `list_metrics` | Your metrics, certified first, with their descriptions and status. |
| `describe_metric` | One metric in words, and every field it can be split or filtered by, with time grains. |
| `query_metrics` | Computes metrics from their definitions, grouped and filtered, and returns the rows plus the SQL that ran. |
| `list_data_models` | Your data models, with their dimensions, measures and joins. |
| `describe_data_model` | One data model in full, including the SQL behind each dimension and measure. |
| `scaffold_data_model` | Drafts a data model from a table’s columns. Saves nothing. |
| `create_data_model` | Creates a new data model. Fails if the name is taken, so it never overwrites one. |
| `create_metric` | Creates a new metric, always as a draft for a person to certify. |

> **Tip: Metrics first**
>
> The tool descriptions tell assistants to reach for `query_metrics` whenever a certified metric fits the question, and to write SQL only when none does. That’s what keeps an assistant’s numbers matching your dashboards.

## Build

| Tool | What it does |
| --- | --- |
| `save_query` | Saves SQL, or a metric query, as a query in Orcabase, optionally with its chart. |
| `list_dashboards` | Lists dashboards. |
| `get_dashboard` | A dashboard and the charts already on it. |
| `create_dashboard` | Creates an empty dashboard. |
| `add_widget` | Pins a saved query’s chart to a dashboard. Without a position, it takes the first free spot. |
| `create_notebook` | Creates an empty notebook. Not available to the built-in agent. |
| `add_notebook_cell` | Adds a SQL cell (saving a new query) or a text cell to a notebook. Not available to the built-in agent. |

## Deliberately left out

There are no tools to edit or delete anything, to certify or deprecate metrics, to add data sources or upload data, or to manage members, tokens and settings. Those stay with people, in Orcabase. See [What it can’t do](https://tini.so/docs/connect-ai#guardrails).

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All docs: https://tini.so/llms.txt