mcp-bigquery-server MCP Server
ergut/mcp-bigquery-server
[](https://agentrank-ai.com/tool/ergut--mcp-bigquery-server/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) A Model Context Protocol (MCP) server that provides secure, read-only access to BigQuery datasets. Enables Large Language Models (LLMs) to safely query and analyze data through a standardized interface.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
ergut/mcp-bigquery-server is a TypeScript MCP server licensed under MIT. A Model Context Protocol (MCP) server that provides secure, read-only access to BigQuery datasets. Enables Large Language Models (LLMs) to safely query and analyze data through a standardized interface. Topics: bigquery, google-cloud, mcp, mcp-servers, model-context-protocol, sql.
Ranked #6108 out of 24846 indexed tools.
Ecosystem
Score Breakdown
148 stars → growing community
Last commit 5mo ago → stale
6/7 issues closed → responsive maintainer
4 contributors → small team
No dependents → no downstream usage
1,793 weekly installs → gaining traction
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
# BigQuery MCP Server <div align="center"> </div> ## What is this? 🤔 This is a server that lets your LLMs (like Claude) talk directly to your BigQuery data — **read-only, with no ability to mutate your warehouse**. Think of it as a friendly translator that sits between your AI assistant and your database, making sure they can chat securely and efficiently. ### Quick Example ```text You: "What were our top 10 customers last month?" Claude: *queries your BigQuery database and gives you the answer in plain English* ``` No more writing SQL queries by hand - just chat naturally with your data! ## How Does It Work? 🛠️ This server uses the Model Context Protocol (MCP), which is like a universal translator for AI-database communication. MCP is supported by Claude Desktop, Claude Code, and a growing number of other AI clients. Here's all you need to do: 1. Set up authentication (see below) 2. Add your project details to your MCP client's config file 3. Start chatting with your BigQuRead full README on GitHub →
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