# Bigquery Mcp

> An MCP server to help AI Agents inspect the contents of a BigQuery warehouse

- **Type:** MCP server
- **Install:** `agentstack add mcp-paddyalton-bigquery-mcp`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [PaddyAlton](https://agentstack.voostack.com/s/paddyalton)
- **Installs:** 0
- **Category:** [Data & Analytics](https://agentstack.voostack.com/c/data-and-analytics)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [PaddyAlton](https://github.com/PaddyAlton)
- **Source:** https://github.com/PaddyAlton/bigquery-mcp

## Install

```sh
agentstack add mcp-paddyalton-bigquery-mcp
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# bigquery-mcp

A Model Context Protocol (MCP) Server for BigQuery.

## Prerequisites

This project and the `mcp` CLI rely on your having the dependency management tool `uv` installed. You can install via e.g. `brew install uv` for Homebrew users. [See here for alternatives](https://docs.astral.sh/uv/getting-started/installation).

This project (currently) assumes you can 'transparently' create a BigQuery `Client`, which is usually the case if you have `gcloud` installed in your local environment. In other environments you may need suitable service account credentials (and you can set the `GOOGLE_APPLICATION_CREDENTIALS` environment variable to indicate the location of these credentials to the BigQuery client library).

### For development

You will also need to have `Taskfile` installed. `brew install go-task` will work if you are a `Homebrew` user.
[See here for alternatives](https://taskfile.dev/installation).

## Quickstart for Cursor IDE

0. ensure you have the prerequisites installed
1. clone down this repository
2. run `uv sync` to install the dependencies
3. in Cursor settings > MCP Servers, start a server with the following command:

`uv run --with mcp --directory /path/to/bigquery-mcp mcp run /path/to/bigquery-mcp/src/server.py`

It is recommended to write a contextual rule in `.cursor/rules/tool-use-rule.mdc` into your working project. The Cursor Agent will need some instructions if it is 
to use the tools properly.

## Details

AI Agents have begun to excel at writing code, but often struggle with data-related tasks. This is because of the coupling between programme logic and the actual contents of the database.

More specifically, AI Agents often fail to write good SQL queries for analysis tasks. They are capable of writing code, so the issue is not a lack of ability in this arena and more due to a lack of context about the _contents_ of the database.

This MCP server assists with this problem area by providing AI Agents with tools they can use to examine the contents of a BigQuery data warehouse (i.e. datasets, tables, columns, query history).

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [PaddyAlton](https://github.com/PaddyAlton)
- **Source:** [PaddyAlton/bigquery-mcp](https://github.com/PaddyAlton/bigquery-mcp)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-paddyalton-bigquery-mcp
- Seller: https://agentstack.voostack.com/s/paddyalton
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.