"Search for information about 'rag'" matching MCP servers:

An agentic AI system that orchestrates multiple specialized AI tools to perform business analytics and knowledge retrieval, allowing users to analyze data and access business information through natural language queries.

Implements a RAG workflow that integrates with any custom knowledge base and can be triggered directly from the Cursor IDE.

Connects a RAG application to open-webui using Model Context Protocol (MCP), enabling server-to-client communication for context retrieval and tool usage in remote environments through Server-Sent Events (SSE).

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.

Enables AI agents to perform web search, extraction, and research across multiple provider backends with persistent multi-key rotation and auditable routing. Supports MCP, CLI, and Agent Skill entry points.

A server that enables document searching using Vertex AI with Gemini grounding, improving search results by grounding responses in private data stored in Vertex AI Datastore.

Enables agents to search across the pooled tools of many connected MCP servers and invoke them through a single endpoint, returning only the handful of tools relevant to each request. Filters by the caller's permissions before ranking, so agents never see or plan around tools their user is not allowed to use.

Enables AI assistants to perform retrieval-augmented generation with hybrid search, reranking, multi-modal image processing, and RAG evaluation through standardized MCP tools.

MCP server providing tools for entity extraction, query refinement, and relevance checking to build Agentic RAG applications.

A meta-MCP server that aggregates authoritative web search and browser research tools, providing a unified interface with a cost-efficient fetch ladder for web research.

An MCP server that exposes an Agno agent with Google Gemini reasoning and Serper web search, enabling MCP-compatible clients like Claude Desktop to perform agent-driven web searches and receive synthesized answers.

A multi-engine web search MCP server that integrates with coding agents, offering parallel search, page fetching, X/Twitter search, deep research, and configurable free/API layers.

An MCP server that enables web search capabilities using OpenAI's o3 model, allowing AI assistants to perform text-based web searches and return AI-powered results.

A Model Context Protocol Server search realtime flight detail with multiple fligh carrier, price , stop , time duration for any given date using simple prompt

Enables AI-powered web searches using Google's Gemini 2.5 models with Google Search Grounding. Supports multiple Gemini models (Flash, Flash-Lite, Pro) with configurable thinking budget and web search capabilities.

Exposes SearXNG web search and query autocomplete to AI clients, returning ranked results, instant answers, and suggestions with filters for category, language, time range, engines, page, and safe search. It is distributed via npx and requires a self-hosted SearXNG instance with the JSON format enabled.

Enables AI agents to drive real Google Chrome with stealth and captcha handling, using Patchright to avoid bot detection.

Enables free-first web search in English and Chinese with no API key required, returning compact multi-source evidence while keeping provider failures, stop reasons, and budget limits visible. Optional paid providers are used only when routing policy and credentials allow.

Enables web search for the pi coding agent using z.ai GLM native search with a DuckDuckGo fallback.