MCP Bigquery Server
MCP BigQuery Server is a lightweight server based on the Go language, supporting querying BigQuery data tables through MCP, and providing functions such as dataset listing, table structure query, and query cost estimation.
rating : 2 points
downloads : 7.2K
What is MCP BigQuery Server?
This is a middleware server designed specifically for BigQuery, allowing developers to access BigQuery data through the standardized Model Context Protocol (MCP). It abstracts the complex BigQuery API into simple command - line operations, especially suitable for users who need to frequently query data but don't want to deal with the details of the underlying API.How to use MCP BigQuery Server?
Just complete three steps: 1) Install via Homebrew. 2) Configure the datasets that are allowed to be accessed. 3) Register the service in the Cursor IDE. Then you can directly query BigQuery data in the editor.Use cases
Data analysts quickly verify data hypotheses, developers directly debug SQL queries in the IDE, and teams share a standardized data query entry.Main features
Dataset whitelist management
Precisely control the scope of accessible datasets through startup parameters to ensure data security
Table structure exploration
Obtain the complete field structure and data types of a table without writing SQL
Query pre - validation
Estimate the query cost and time before execution to avoid unexpectedly high fees
Advantages
Implemented in lightweight Go language, starts quickly and has low resource consumption
Deeply integrated with Cursor IDE to provide a seamless development experience
Fine - grained access control, only exposes approved datasets
Limitations
Currently only supports basic query functions, does not support advanced operations such as streaming writes
Requires pre - configuration of the dataset whitelist, with some limitations in flexibility
Relies on Homebrew for installation, Windows users need to download manually
How to use
Install the service
One - click installation via the Homebrew package manager
Configure datasets
Specify the Google Cloud project and datasets that are allowed to be accessed in the startup command
IDE integration
Register the service endpoint in the mcp.json configuration file of Cursor
Usage examples
Data exploration
Quickly understand available data resources when taking over a new project
Query optimization
Verify SQL syntax and estimate costs before formal execution
Frequently asked questions
How to add a new dataset to the whitelist?
Is the billing for dry_run_query real?
Related resources
GitHub repository
Project source code and the latest version
BigQuery documentation
Official SQL syntax reference

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