"Agentic RAG: Understanding or Exploring Its Meaning and Applications" matching MCP servers:

Enables agents to control a real Chromium browser with semantic tools, providing compact observations and outcome-verified actions for web interaction tasks.

Lets many AI agent sessions share one real logged-in browser, each with its own tab group, using standard Playwright MCP tools.

Enables AI agents to search the web with clean page text, crawl websites into Markdown, extract articles and structured data, and monitor Google News and press releases for LLM context and RAG pipelines. It works with MCP clients and uses the user's own Apify API token for pay-per-result data retrieval.

Enables MCP clients to automate a real Chrome browser via Playwright, supporting session sharing and tools for navigation, clicking, typing, and more.

Enables multiple agents to share a single Chrome browser with isolated tabs and shared sessions, allowing coordinated browsing and automation.

Enables an AI agent to observe, plan, and act inside a real browser session by exposing navigation, snapshot, click, type, and screenshot MCP tools over local JSON-RPC and SSE. It runs a Playwright-backed browser in-process and provides stable element references for reliable actions.

Enables MCP-compatible AI agents to inspect, read, close, deduplicate, group, and consolidate live Chromium browser tabs through a secure local bridge, with safety checks and no need for its own AI model or API key.

Fetches web content and returns relevant chunks using RAG with semantic chunking, query-based scoring, and LexRank, supporting PDFs and 50+ languages.

Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.

Enables web search via Serper API with advanced search operators and webpage scraping capabilities to extract content in plain text or markdown format.

Provides AI agents and assistants with advanced web crawling and RAG capabilities, enabling them to scrape websites and perform semantic search over crawled content.

A local MCP server that connects to a Chrome extension to enable AI agents to control browser tabs, execute automation, and interact with web pages via tools.

A fault-tolerant, stealth-enabled Model Context Protocol (MCP) server for web searching and content fetching. Built for AI Agents (Cursor, Claude Code, OpenCode), it uses a stealth browser engine to fetch pages, dynamically handles SPAs/React, and converts bloat into token-optimized Markdown.

Exposes Amazon Nova Act web automation capabilities through the Model Context Protocol, enabling AI agents to perform browser tasks like navigation, data extraction, and form interaction.

Maps Electron app IPC handlers to MCP tools and provides 33 built-in CDP tools for DOM automation, screenshots, interaction, and debugging, enabling Claude Code to directly control your Electron app.

Provides web search and page fetching capabilities using Ollama's API.

Provides AI agents with complete web search, crawling, and RAG capabilities through a Docker-based solution combining Model Context Protocol, Crawl4AI, SearXNG, and Supabase.

Enables users to get real-time weather information for Israeli cities through MCP tools, using Playwright to scrape live data and provide it to the language model.

MyChart MCP Server

Enables viewing your own LinkedIn account data—such as profile views, applications, saved jobs, job listings, and notifications—as structured tool results, with optional gated write actions for saving or unsaving jobs and unfollowing companies.