"Local RAG system for providing documentation to a large language model (LLM)" matching MCP servers:

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

Enables local web crawling and scraping through MCP, providing tools to fetch pages as Markdown, extract structured data with CSS selectors, and capture full-page screenshots while managing a shared browser instance.

Enables users to run shell commands with compressed output, extract information from large files, drive local opencode and Codex agents, perform browser-automation tasks, and monitor runs via a live dashboard.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

MCP server for the LLM Wiki Chrome extension that exposes bounded browser automation tools (shared tabs, accessibility snapshots, screenshots, clicks, typing, etc.) with explicit user consent and strict typing, enabling local agents to interact with specific web pages via a native messaging relay.

A server that enables browser-based local LLM inference using Playwright to automate interactions with @mlc-ai/web-llm, supporting text generation, chat sessions, model switching, and status monitoring.

Enables Claude to fetch web pages from the user's own local network connection instead of AI datacenter IPs, including optional authenticated sessions, with verdicts for bot challenges, login walls, and other failures.

MCP server for local web search via SearXNG, providing unlimited queries without API keys or cost, with automatic fallback to public instances.

Enables MCP-capable agents to fetch public pages, extract business signals and FAQ content, score a local business's web presence from 0-10, and generate a sales-ready audit with ranked gaps and a recommended offer.

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 AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Enables agents to perform local metasearch, scholarly and code/model lookups, and fetch rendered web pages or PDFs as paginated markdown, including stealth browsing and arXiv paper overviews.

Gives Claude control of a real, headed Chromium browser via Playwright, enabling web navigation, clicking, typing, screenshots, and JavaScript evaluation.

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

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

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 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 users to discover jobs by target titles and countries, rank job descriptions by skill coverage across all imported resumes, generate tailored ATS-ready resumes and cover letters, and fill and submit requested application batches through a signed-in AI host with browser access.

Enables AI agents to work with declarative adapters and sanitized capture fixtures for resume autofill, without access to the encrypted browser vault.

It enables AI agents to call a small set of reliable, permission-aware tools generated from an existing website through the Model Context Protocol, without rebuilding the site.

MCP server that fetches remote or local HTML resources and converts them to Markdown, enabling AI clients to summarize or process web content.

Enables MCP clients to run SearXNG-backed public web searches and Crawl4AI page extraction for approved domains, with local approvals, deny rules, audit history, and optional OpenAI Secure MCP Tunnel connectivity.

Enables users to record, review, verify, and expose permitted browser workflows as callable MCP tools with typed inputs, isolated Chromium verification, and approval-gated writes.

Lightweight MCP server for controlling a Windows Chrome instance from WSL, designed for AI coding agents with minimal token overhead and human-in-the-loop support.

Enables tool-calling LLMs to search the internet, capture website images, extract webpage text, and more via a local MCP server.

Enables converting webpages into structured JSON using CSS-selector schemas, with anti-bot handling and support for protected pages.

Converts WeChat Official Account articles to clean Markdown with locally downloaded images, supporting single and batch operations via MCP tools.

Enables converting any webpage to clean LLM-ready markdown, with extraction, article, and news modes, using a real browser with anti-bot handling.

MCP server that gives AI agents safe, snapshot-based control of a local Chromium browser to publish user content to registered platforms, with strict privacy boundaries and human handoff for final actions.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.