MCP Directory

BigQuery MCP server

Inspect BigQuery schemas and run SQL queries from your LLM client.

Unverified
stdio (local)
No auth
Python
View repo 127

Add to your client

Copy the config for your MCP client and paste it into its config file.

Install / run
npx -y @smithery/cli install mcp-server-bigquery --client claude

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "bigquery-mcp-server": {
      "command": "uvx",
      "args": [
        "mcp-server-bigquery"
      ],
      "env": {
        "BIGQUERY_PROJECT": "{{GCP_PROJECT_ID}}",
        "BIGQUERY_LOCATION": "{{GCP_LOCATION}}"
      }
    }
  }
}

Requires `uv` (the Python package runner). Install it from https://docs.astral.sh/uv/ if `uvx` is not found.

Before you start

  • A Google Cloud project with BigQuery enabled
  • GCP credentials: a service account key file or default application credentials
  • uvx (uv) available to run the server, or Smithery CLI to install

About BigQuery MCP server

BigQuery MCP server is a Python-based Model Context Protocol server that gives LLMs access to Google BigQuery. It lets a connected client inspect database schemas and execute SQL queries in the BigQuery dialect. Configuration is supplied via command line arguments or environment variables, including the required GCP project ID and location, plus optional dataset filtering, a service account key file, and a query timeout.

Tools & capabilities (3)

execute-query

Executes a SQL query using the BigQuery dialect.

list-tables

Lists all tables in the BigQuery database.

describe-table

Describes the schema of a specific table.

What this server can do

BigQuery MCP server provides tools for these capabilities — tap one to see every MCP server that does the same:

Inspect database schema

When to use it

  • Ask an LLM to query data in BigQuery using natural language
  • Inspect the schema of BigQuery tables before writing queries
  • Explore available tables across one or more datasets in a GCP project
  • Run analytical SQL against BigQuery directly from Claude Desktop, Claude Code, or Cursor

Security notes

Authenticates to BigQuery using a service account key file (--key-file / BIGQUERY_KEY_FILE) or the environment's default GCP credentials. Use --dataset / BIGQUERY_DATASETS to restrict which datasets are exposed to the LLM.

BigQuery MCP server FAQ

How do I authenticate to BigQuery?

Provide a service account key file via the --key-file argument or BIGQUERY_KEY_FILE environment variable. If not provided, the server uses the environment's default GCP credentials.

Can I limit which datasets the server can access?

Yes. Use the --dataset argument (repeatable) or the BIGQUERY_DATASETS environment variable (comma-separated) to restrict the server to specific datasets. If omitted, all datasets in the project are considered.

Which configuration values are required?

The GCP project ID (--project / BIGQUERY_PROJECT) and the GCP location (--location / BIGQUERY_LOCATION) are required. Dataset filtering, key file, and timeout are optional.

#bigquery#sql#database#gcp#google-cloud#analytics

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