BigQuery MCP server

@MCP-Mirror

About BigQuery MCP server

Mirror of

#bigquery #mcp-server #data-access

Basic information

Category

Databases

Transports

stdio

Publisher

MCP-Mirror

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "LucasHild_mcp-server-bigquery": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

Tools

3

Executes a SQL query using BigQuery dialect

Lists all tables in the BigQuery database

Describes the schema of a specific table

Overview

What is BigQuery MCP server?

A Model Context Protocol server that gives LLMs access to Google BigQuery. It lets AI assistants inspect database schemas and execute SQL queries directly against BigQuery datasets.

How to use BigQuery MCP server?

Install via uvx mcp-server-bigquery and configure it in your MCP client (e.g., Claude Desktop) by passing --project (required), --location (required), and optionally --dataset (repeatable). The server runs over stdio and exposes three tools.

Key features of BigQuery MCP server

Execute arbitrary SQL queries using BigQuery dialect
List all tables in the configured project/datasets
Describe the schema of a specific table
Filter which datasets are available to the LLM
Published on PyPI for easy installation

Use cases of BigQuery MCP server

Let an LLM assistant answer natural-language questions by querying BigQuery
Automate schema discovery and documentation generation
Build a natural-language interface for business analysts to explore data
Integrate BigQuery querying into AI-powered coding or analysis workflows

FAQ from BigQuery MCP server

What tools does BigQuery MCP server provide?

It provides three tools: execute-query, list-tables, and describe-table.

How do I restrict which datasets the server can access?

Use the --dataset argument (repeatable) to specify one or more datasets. If omitted, all tables in the project are considered.

What are the required configuration arguments?

You must provide --project (the GCP project ID) and --location (the GCP location, e.g. europe-west9).

Is BigQuery MCP server published on PyPI?

Yes. It can be run via uvx mcp-server-bigquery without a local checkout.

How can I debug the server?

Use the MCP Inspector. Run npx @modelcontextprotocol/inspector uv --directory <PATH> run mcp-server-bigquery to get a debugging URL.

Comments

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