"Google BigQuery" matching MCP servers:

Enables LLMs to explore BigQuery datasets and tables, run safe read-only queries, and optionally perform vector search using BigQuery embeddings.

This is a server that lets your LLMs (like Claude) talk directly to your BigQuery data! Think of it as a friendly translator that sits between your AI assistant and your database, making sure they can chat securely and efficiently.

A Model Context Protocol server that provides access to BigQuery. This server enables LLMs to inspect database schemas and execute queries.

Enables secure access to BigQuery datasets with intelligent query result caching, schema evolution tracking, and AI-powered query optimization recommendations through Supabase integration.

Enables MCP-compatible reasoning agents to perform read-only discovery, retrieval, and exact search across Google Drive, Docs, Sheets, and Slides through a stateless Cloud Run service.

A local MCP server that enables LLMs to securely search and read files within designated Google Drive folders. Supports Google Docs, Google Sheets, PDFs, and plain text with strict folder-scoping via service account authentication.

This MCP server provides comprehensive Google Workspace integration (Gmail, Drive, etc.) with multi-user OAuth. Unique features include RAG-powered natural language to Chat card rendering, runtime Jinja2 macro creation, and dynamic tool management.

MCP server for querying your local Google Takeout activity (Search/YouTube history) via SQLite/FTS5. Provides tools for keyword search, activity stats, and database info, enabling AI assistants to cite your personal history.

A stdio MCP server that provides a single tool to query Gemini with Google Search grounding for current web information, returning synthesized answers with source links.

An MCP-based conversational HR agent that handles time tracking queries, policy lookups, adjustment approvals with human confirmation, and BigQuery analytics via natural language.

Query SQL databases (SQLite, PostgreSQL, BigQuery, Databricks) in natural language through a business semantic layer — glossary, metrics, and a data dictionary grounded against your real schema. Read-only by default, with an embedded SQLite + sqlite-vec metadata store and no external infra required.

Natural language to SQL engine with multi-connector support (PostgreSQL, MySQL, Snowflake, BigQuery, DuckDB), document QA, semantic caching, and self-hosted MCP server.

An MCP server that provides Google Search functionality with automatic API key rotation and intelligent quota management, enabling natural language search queries with advanced filtering options.

Provides AI-powered search and documentation tools using Google Vertex AI or Gemini API with real-time web search grounding, enabling technical queries, code analysis, documentation retrieval, and architecture recommendations to overcome LLM knowledge gaps.

Fetches news articles from Google News, vectorizes them locally using ChromaDB, and enables semantic search through natural language queries.

An MCP server that enables AI models to perform Google Web searches using the Gemini API, complete with citations and grounding metadata for accurate information retrieval. It is compatible with Claude Desktop and other MCP clients for real-time web access.

A Model Context Protocol server that enables LLMs to perform web searches using Google's Custom Search API through a standardized interface.

Open-source agentic schema layer. Define metrics once in YAML, query governed data from any warehouse (Snowflake, BigQuery, Databricks, PostgreSQL, DuckDB) via MCP.

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.

A Model Context Protocol server that enables Claude to perform Google Custom Search operations by connecting to Google's search API.