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MCP BigQuery Server

MCP BigQuery Server

Local
github.com/monochromeganeDatabases0Updated 81w ago
Repository

About MCP BigQuery Server

MCP BigQuery Server is a lightweight MCP server written in Go for querying BigQuery dataset and table information. It is for users who need to inspect schemas or estimate query cost and time before running a query.

Key features

  1. 01List allowed datasets
  2. 02List tables in a dataset
  3. 03Get table schemas
  4. 04Dry-run queries for cost and time estimates

Use cases

  1. 01Review accessible datasets
  2. 02Inspect a table's schema
  3. 03Estimate query cost and time before execution

MCP support

The MCP server exposes tools for listing BigQuery datasets and tables, retrieving table schemas, and dry-running queries.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP BigQuery Server

Actions Status

Overview

MCP BigQuery Server is a server that allows you to query BigQuery tables using MCP. Written in Go, it's lightweight and easy to install with just a few commands.

Installation

$ brew tap monochromegane/tap
$ brew install monochromegane/tap/mcp-bigquery-server

Available Tools

  • list_allowed_datasets: Get a listing of all allowed datasets.
  • list_tables: Get a detailed listing of all tables in a specified dataset.
  • get_table_schema: Get the schema of a specified table in a specified dataset.
  • dry_run_query: Dry run a query to get the estimated cost and time.

Registration

To use MCP BigQuery Server in Cursor, add the following configuration to your .cursor/mcp.json:

{
  "mcpServers": {
    "BigQuery": {
      "command": "mcp-bigquery-server",
      "args": [
        "start",
        "--project",
        "sample-project",
        "--dataset",
        "test1",
        "--dataset",
        "test2"
      ]
    }
  }
}

Note: You can specify multiple datasets by repeating the --dataset argument.

License

MIT

Author

monochromegane

Comments

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