Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL.
Provides read-only access to Google BigQuery, enabling discovery of datasets, tables, schemas, partitioning, freshness, scheduled queries, notebooks and code assets, and execution of validated SELECT queries under the user's Google credentials.
A read-only Model Context Protocol server over Google BigQuery that lets AI clients answer plain-language data questions by discovering schemas, inspecting table freshness and code assets, and running validated SELECT queries under the user's own Google credentials.
14
53 PyPI
MIT
Why this server?
Enables AI agents to interact with Google BigQuery databases, including listing tables, retrieving schemas, and executing SQL queries.
Connects MCP clients to databases like Snowflake, BigQuery, and Databricks through Alkemi's data platform, enabling natural language database queries with proper schema understanding and metadata management for consistent team-wide access.
51 npm
4
MIT
Why this server?
Provides an interface for AI agents to query Google BigQuery datasets using consistent metric definitions.
Open-source agentic schema layer. Define metrics once in YAML, query governed data from any warehouse (Snowflake, BigQuery, Databricks, PostgreSQL, DuckDB) via MCP.
28
Apache 2.0
Why this server?
Allows searching 100M+ patents via Google BigQuery's public patent dataset by keywords, CPC/IPC codes, or full-text queries. Provides tools for prior art search and patent retrieval.
An MCP server that enables patent creation and analysis, including regulation search, prior art discovery, claim compliance checks, and patent diagram generation, all within Claude Code.
200
MIT
Why this server?
Supports Google BigQuery dialect for SQL generation, schema introspection, validation, and transpilation.
An MCP server that provides SQL generation, validation, transpilation, and schema introspection across 10 SQL dialects, using a property graph schema and phase-locked reasoning to convert natural language to accurate SQL.
3
MIT
Why this server?
Enables natural language querying and secure SQL execution against BigQuery datasets, allowing users to ask questions in plain English and retrieve results.
Production-ready MCP server for BigQuery that translates natural language questions to SQL, executes queries securely, and delivers results via stdio or HTTP for integration with GitHub Copilot, Power BI, and web applications.
1,651 npm
MIT
Why this server?
Provides tools for querying and analyzing Google BigQuery data, including schema browsing, query execution, dataset comparison, and data sampling.
Enables AI assistants to query and analyze Google BigQuery data, including schema browsing, running queries, and comparing datasets through natural language.
MIT
Why this server?
Provides access to bulk patent data via Google BigQuery, enabling large-scale patent analysis.
