Bigquery MCP

Name: Bigquery MCP
Author: SnowLeopard-AI

by SnowLeopard-AIversion 0.1.1i★ –iRuns on your computer

Registry nameio.github.SnowLeopard-AI/bigquery-mcp

Install

Overview

Description from the maker (original English)

A SnowLeopardAI-managed MCP server that provides access to Google BigQuery data.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Databases & datasets

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "bigquery": {
      "command": "uvx",
      "args": [
        "sl-bigquery-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add bigquery -- uvx sl-bigquery-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "bigquery": {
      "command": "uvx",
      "args": [
        "sl-bigquery-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "bigquery": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "sl-bigquery-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account SnowLeopard-AI, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Databases & datasetsi

More stars than 0% of the other 955 servers in this category
Published to the registry more recently than 7% of the other 955 servers in this category
Basic checks equal to or better than 100% of the other 955 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Bigquery MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by supabase

Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.

Computer or cloud★ 2,993Apache-2.0Updated yesterday

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Snow Leopard BigQuery MCP

A Model Context Protocol (MCP) server for Google BigQuery that enables AI agents to interact with BigQuery databases through natural language queries and schema exploration.

This project was developed by Snow Leopard AI as a benchmarking tool for our platform, and we're making it publicly available for the community to use and build upon.

What is MCP?

The Model Context Protocol (MCP) is an open standard that allows AI applications to securely connect to external data sources and tools. This BigQuery MCP server acts as a bridge between AI agents and your BigQuery datasets.

Snow Leopard BigQuery MCP Server Features

Resources

Resource URI	Description
`bigquery://tables`	List all tables available to the agent
`bigquery://tables/{table}/schema`	Get the schema of a specific table

Tools

Tool	Description
`list_tables(table: str)` (optional)	List available tables
`get_schema(table: str)` (optional)	Get the schema of a given table
`query(sql: str)`	Execute BigQuery SQL and return results

Quick Start: Claude Desktop

Prerequisites

Before getting started, ensure you have:

Claude Desktop: Download here
Google Cloud Project with BigQuery enabled: Setup guide
Google Cloud CLI (gcloud): Installation guide
UV Package Manager: Installation guide

1. Setup Google Cloud

First, we need to authenticate with Google.

gcloud auth application-default login

This opens your browser to authenticate your local machine with Google Cloud.

2. Configure Claude Desktop

Edit your claude_desktop_config.json file to add the BigQuery MCP server.

Application: Claude > Settings > Developer > Edit Config Mac: ~/Library/Application\ Support/Claude/claude_desktop_config.json Windows: %APPDATA%\\Claude\\claude_desktop_config.json

You will need to set your project to a Google Cloud project with permissions to submit bigquery jobs. If you do not have a project that you can run bigquery jobs on, create and test one by following Google's BigQuery Quickstart Guide Create a project and follow the instructions to query a public dataset.

"mcpServers": { "bigquery": { "command": "uvx", "args": [ "sl-bigquery-mcp", "--dataset", "bigquery-public-data.usa_names", "--project", "🚨 🚨" ] } } }

3. Close Claude Desktop and Launch it from the terminal

Depending on how you have installed uv, the uvx executable may not be in Claude Desktop's PATH if it is launched from the GUI. To be sure uvx is accessible from Claude Desktop, let's run it in the terminal.

open -a claude

After saving the configuration, restart Claude Desktop. You should now be able to ask Claude questions about your BigQuery data!

Example Query

What are the top 10 most popular names in 2020?

Configuration Options

To see a complete list of parameters:

uvx sl-bigquery-mcp --help

Usage: sl-bigquery-mcp [OPTIONS]

╭─ Options ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ --mode [stdio|sse|streamable-http] MCP transport protocol [default: stdio] │ │ --dataset TEXT Dataset(s) for mcp resources. Will create resources for all tables. │ │ --table TEXT Table(s) for mcp resources. Can be specified as project.dataset.table or dataset.table │ │ --enable-list-tables-tool --no-enable-list-tables-tool Registers list_resources tool [default: enable-list-tables-tool] │ │ --enable-schema-tool --no-enable-schema-tool Registers get_schema tool [default: enable-schema-tool] │ │ --project TEXT BigQuery project [env var: BQ_PROJECT] [default: None] │ │ --api-method [INSERT|QUERY] BigQuery client api_method [default: QUERY] │ │ --port INTEGER [default: 8000] │ ╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Troubleshooting / FAQ

An MCP Error has occurred

First, check out your Claude Desktop app logs (in the same directory as the config file) for more verbose errors / logging

On Startup

This usually means Claude is having issues starting the mcp server. Frequently this is due to uvx being inaccessible from the application. In this case, use the full path to your uvx executable instead of just uvx in claude_desktop_config.json.

To find your uv executable, run

which uvx

Otherwise, this may be caused by bad arguments, dependency version incompatibilities, or bugs. If you run into the last two, please file an issue describing the problem.

On Resource / Tool Usage

This may be a misconfiguration mcp server, authentication issues, the llm getting too much data, or of course, product bugs. After checking the logs, consider using the MCP Inspector to debug your issue. And of course, file any bugs you find on our issue board.

Local Development & Testing

Setup Development Environment

Clone the repository
Setup virtual environment and install dependencies
Verify installation

git clone https://github.com/SnowLeopard-AI/bigquery-mcp.git

cd bigquery-mcp

uv sync source .venv/bin/activate

sl-bigquery-mcp --help

Authenticate with Google Cloud

The following command will launch a browser for you to login to your google cloud account. You must have a Google Cloud project with BigQuery enabled. If you don't, see Google's bigquery setup guide.

gcloud auth application-default login

gcloud config set project gcloud auth application-default set-quota-project

Running Tests

Run the tests to make sure your dev environment is properly configured.

pytest tests

_Note: the tests run actual BigQuery queries against public datasets and require authentication._

Local MCP Inspector

For hands-on testing and development, use the MCP Inspector tool:

npx @modelcontextprotocol/inspector uv run sl-bigquery-mcp --dataset bigquery-public-data.usa_names

Contributing

We welcome contributions! Please coordinate with us on discord to ensure your changes can quicly make it into the repo. Communicating before coding always saves time.

For logistics of contributing to an open source project, see the first contributions repository.

Support

Issues: GitHub Issues Documentation: BigQuery Documentation MCP Protocol: Model Context Protocol Contact: Discord Server

Bigquery MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Databases & datasetsi

Common questions

Alternatives

Supabase

MongoDB MCP Server

Elasticsearch MCP Server

README from the maker

What is MCP?

Snow Leopard BigQuery MCP Server Features

Resources

Tools

Quick Start: Claude Desktop

Prerequisites

1. Setup Google Cloud

2. Configure Claude Desktop

3. Close Claude Desktop and Launch it from the terminal

Example Query

Configuration Options

Troubleshooting / FAQ

An MCP Error has occurred

On Startup

On Resource / Tool Usage

Local Development & Testing

Setup Development Environment

Authenticate with Google Cloud

Running Tests

Local MCP Inspector

Contributing

Support