"Google search engine" matching MCP servers:

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.

Enables deep web search across multiple providers including Google, Bing, Brave, DuckDuckGo, and Perplexity, with support for comprehensive AI-powered research using intelligent multi-engine 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.

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

A tiny RAG-lite retrieval engine that indexes files on disk and provides semantic search via MCP, returning relevant text chunks (file, line, score) without generating answers.

Multi-engine aggregated search MCP server that combines results from 7 search engines with deduplication, relevance ranking, and web page content extraction.

🔍 High-Availability Multi-Engine Search Aggregation MCP Server - Intelligent Failover, Unified API, LLM-Optimized Content Processing.

High-speed Google search intelligence and token-optimized Markdown grounding engine for AI LLMs, autonomous agents, and RAG pipelines.

An MCP server that enables natural language interaction with Google's Discovery Engine API, allowing users to search, recommend, and manage data through conversational interfaces.

Provides a Google search tool via the Serper API, returning structured results and a summary answer for LLMs like Claude.

Enables integration of Google search functionality into MCP-enabled applications using the Serper API, providing rich search results, configurable parameters, and efficient response handling.

Exposes an internal engineering knowledge base to AI assistants, allowing users to search and retrieve standards, runbooks, and architecture decisions. It supports RAG-enhanced search, document scraping, and specialized prompts for incident investigation and code reviews.

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 personal memory engine and MCP server that stores durable facts in markdown files managed via git, enabling hybrid search (lexical + semantic) through an MCP interface for persistent context across LLM sessions.

Enables grounded, dated research from a curated AI-knowledge repository, offering free BM25 retrieval and a research loop that combines the knowledge base, curated sources, and the open web with tiered citations.

Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.

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.

Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.