Bigquery MCP Server
vendor.bigquery/mcp
answering
Bigquery is answering right now. Last checked 7 min ago. It exposes 6 tools.
Uptime history
31 hours of history
31 hours agonow
100.0%
Uptime 24h
91 of 91 checks
6
Tools
read from the server
52 ms
Response time
average over 24h
open, no key
Access
streamable-http
Connect this server
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 7 min ago.
run in your terminal
claude mcp add mcp --transport http https://bigquery.googleapis.com/mcp~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"mcp": {
"url": "https://bigquery.googleapis.com/mcp"
}
}
}~/.codex/config.toml
[mcp_servers.mcp]
url = "https://bigquery.googleapis.com/mcp".cursor/mcp.json
{
"mcpServers": {
"mcp": {
"url": "https://bigquery.googleapis.com/mcp"
}
}
}.vscode/mcp.json
{
"mcpServers": {
"mcp": {
"url": "https://bigquery.googleapis.com/mcp"
}
}
}Available tools 6
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
dataset
get_dataset_info
Get metadata information about a BigQuery dataset.
list_dataset_ids
List BigQuery dataset IDs in a Google Cloud project.
Supports pagination. Use `page_size` to limit results and `page_token` to retrieve next page.
execute
execute_sql
Run a SQL query in the project and return the result. Prefer the `execute_sql_readonly`
tool if possible.
This tool can execute any query that bigquery supports including:
* SQL Queries (SELECT, INSERT, UPDATE, DELETE, CREATE, etc.)
* AI/ML functions like AI.FORECAST, ML.EVALUATE, ML.PREDICT
* Any other query that bigquery supports.
Example Queries:
-- Insert data into a table.
INSERT INTO `my_project.my_dataset`.my_table (name, age)
VALUES ('Alice', 30);
-- Create a table.
CREATE TABLE `my_project.my_dataset`.my_table (
name STRING,
age INT64);
-- DELETE data from a table.
DELETE FROM `my_project.my_dataset`.my_table WHERE name = 'Alice';
-- Create Dataset
CREATE SCHEMA `my_project.my_dataset` OPTIONS (location = 'US');
-- Drop table
DROP TABLE `my_project.my_dataset`.my_table;
-- Drop dataset
DROP SCHEMA `my_project.my_dataset`;
-- Create Model
CREATE OR REPLACE MODEL `my_project.my_dataset.my_model`
OPTIONS (
model_type = 'LINEAR_REG'
LS_INIT_LEARN_RATE=0.15,
L1_REG=1,
MAX_ITERATIONS=5,
DATA_SPLIT_METHOD='SEQ',
DATA_SPLIT_EVAL_FRACTION=0.3,
DATA_SPLIT_COL='timestamp') AS
SELECT col1, col2, timestamp, label FROM `my_project.my_dataset.my_table`;
Queries executed using the `execute_sql` tool will have the job label
`goog-mcp-server: true` automatically set. Queries are charged to the project specified
in the `projectId` field.
execute_sql_readonly
Run a read-only SQL query in the project and return the result. Prefer this tool over
`execute_sql` if possible.
This tool is restricted to only `SELECT` statements. `INSERT`, `UPDATE`, and `DELETE`
statements and stored procedures aren't allowed. If the query doesn't include a `SELECT`
statement, an error is returned. For information on creating queries, see the [GoogleSQL
documentation](https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax).
Example Queries:
-- Count the number of penguins in each island.
SELECT island, COUNT(*) AS population
FROM bigquery-public-data.ml_datasets.penguins GROUP BY island
-- Evaluate a bigquery ML Model.
SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`)
-- Evaluate BigQuery ML model on custom data
SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`,
(SELECT * FROM `my_dataset.my_table`))
-- Predict using BigQuery ML model:
SELECT * FROM ML.PREDICT(MODEL `my_dataset.my_model`,
(SELECT * FROM `my_dataset.my_table`))
-- Forecast data using AI.FORECAST
SELECT * FROM AI.FORECAST(TABLE `project.dataset.my_table`, data_col => 'num_trips',
timestamp_col => 'date', id_cols => ['usertype'], horizon => 30)
Queries executed using the `execute_sql_readonly` tool will have the job label
`goog-mcp-server: true` automatically set. Queries are charged to the project specified
in the `projectId` field.
table
get_table_info
Get metadata information about a BigQuery table.
list_table_ids
List table ids in a BigQuery dataset.
Supports pagination. Use `page_size` to limit results and `page_token` to retrieve next page.
Endpoints
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://bigquery.googleapis.com/mcp | streamable-http | answering | 53 ms | 7 min ago |
Bigquery — questions
Answers built from our own checks of this server.
What can Bigquery do?
It exposes 6 tools, read directly from the server on our last check. Among them: execute_sql, execute_sql_readonly, get_dataset_info, get_table_info, list_dataset_ids, list_table_ids. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README.
How MCP servers expose tools in the first place →
What is Bigquery mostly used for?
Its tools cluster around execute, dataset and table. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is Bigquery working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 52 ms. The bar chart above shows every period we have measured.
How do I connect Bigquery?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Bigquery need an API key?
No. Bigquery completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 6 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Bigquery?
It answers our handshake in 52 ms on average, which is faster than 97% of all working MCP servers we measure. That puts it in the quick quarter of the ecosystem. The comparison comes from our own checks across the whole registry, every 15 minutes.