# BigQuery through toolfare

> The datasets in your BigQuery project, the tables and views inside each one, and every column’s name and type — answered inside ChatGPT, Claude, Codex or Cursor, so the person writing the query starts from the real schema. Connect BigQuery to toolfare once; your AI reads it with your own credentials, and every read is free.

Page: https://toolfare.ai/bigquery

## Use it from your agent

Paste this into Claude Code, Codex, Cursor or any agent with a shell:

> Set up https://toolfare.ai/skill.md, then use toolfare to answer: What datasets do we have in BigQuery?

Apps without a terminal connect toolfare as an MCP server: https://toolfare.ai/docs#connect

## Use it from a script

```sh
mkdir -p ~/.local/bin
curl -fsSL 'https://toolfare.ai/toolfare/toolfare.mjs' -o ~/.local/bin/toolfare
chmod +x ~/.local/bin/toolfare
export PATH="$HOME/.local/bin:$PATH"
export TOOLFARE_MCP_URL='https://api.toolfare.ai/mcp'
toolfare login
```

Then connect your BigQuery account in the toolfare console (https://toolfare.ai/bigquery#setup); calls fail until it is connected.

Sign in once per machine; the CLI renews the sign-in itself. On a CI runner or another server, create an API key in the toolfare console and set it as `TOOLFARE_API_KEY` instead of signing in. Paid calls on one sign-in or key run one at a time. `--max-cost` refuses a call quoted above that many credits (1,000 credits = $3).

## Tools

### The datasets in a project

Tool: `bigquery_list_datasets`

Every dataset the connection can see, with its region — the starting point for knowing what data exists at all.

Ask:
- What datasets do we have in BigQuery?
- Which of our datasets are in the EU region?

### The tables and views inside a dataset

Tool: `bigquery_list_tables`

Tables, views, materialised views and external tables in one dataset, each with its type — views are often the curated entry point, and they are listed alongside tables.

Ask:
- What tables are in our marketing dataset?
- Is there a view for daily revenue in the analytics dataset?

### Every column’s name and type

Tool: `bigquery_get_table_schema`

A table or view’s columns — name, type and mode, with nested fields one level deep — plus its row and byte counts.

Ask:
- What columns does the orders table have?
- How many rows are in the sessions table, and how big is it?

### Also available

- `bigquery_list_projects`: Projects available through your connection

## Price

Free to read: it is your own account, so toolfare pays nobody for the data and charges nothing per read. No per-read charge to observe. Reads need no purchase. Like every toolfare call, they run only while your balance holds at least $0.003, and that is not spent.

Balances and top-ups are in US dollars. Quotes and `--max-cost` count credits: 1,000 credits = $3 ($0.003 each).

## Use it when

- You are about to write SQL and want the real column names rather than a guess.
- You want to know which dataset or view holds the numbers you are after.
- You are checking how large a table is before querying it.

## Look elsewhere when

- You want the rows themselves. Running SQL needs a person to review the query first, and that step is not published through the MCP connection.
- You want marketing numbers that already have a source. Your ad and analytics accounts answer those directly.

## Limits

- The connection lists datasets, tables and schemas; it does not run queries or return table rows.
- Listing a table does not prove it is readable — row-level permission is checked only when a query runs.
- Nested columns are expanded one level deep.