"Open source MCP (Model Context Protocol) implementations" matching MCP servers:

A server that enables language models to perform web searches through SearXNG using the Model Context Protocol standard.

Read-only MCP server providing AI access to verifiable web, GitHub, and local sources, plus a managed fantasy entity catalog, with strong security and provenance tracking.

AIFeed Open Standard. AIFeed Protocol to the building tools section. AIFeed enables web publishers to provide verified, token-efficient content feeds for AI agents.

Searches job listings from Taiwanese job boards (104 and Yourator) and returns normalized results.

Provides live web and document intelligence, including search, company news, scraping, crawling, structured extraction, document parsing, brand intelligence, screenshots, website monitoring, and batch jobs.

An MCP server that builds structured research source packs for a topic, extracting verified facts, quotes, numbers, dates, and primary links with a coverage map of claims across sources.

Enables AI agents to automate both web browsers and native desktop applications through a unified interface, supporting tasks like browsing, clicking, typing, and file clipboard operations via exposed MCP tools.

An MCP server that fetches web pages and extracts clean, AI-usable context from them, enabling tools for link discovery, content search, and integrated fetch-and-search operations.

Enables Claude to delegate web search, page reading, text drafting, and parallel multi-model image generation to cheaper helper models on any OpenAI-compatible backend. Claude stays in charge of planning and final decisions while consuming fewer of its own tokens.

Web search using free multi-engine search (NO API KEYS REQUIRED) — Supports Bing, Baidu, DuckDuckGo, Brave, Exa, and CSDN.

Enables AI agents to control the user's Chrome or Firefox browser, leveraging existing sessions for tasks requiring authentication and user handoff.

Exposes runtime-local capabilities from browsers, apps, devices, and local processes to AI agents through a unified MCP bridge, enabling path-based discovery and invocation of live context.

A read-only MCP server that gives AI agents the web as compact, ranked, verified evidence — no API keys, no cloud retrieval, all models local.

Enables AI assistants to inspect React component trees, props, state, and source locations in Chrome, facilitating UI debugging and analysis.

MCP server that gives any LLM a managed Docker workspace with live browser, terminal, code execution, document skills, and autonomous sub-agents.

A proxy-aware MCP server that enables web searching across multiple engines and automated markdown content extraction from webpages. It features a deep research agent for recursive searching and synthesis, supporting complex network environments through SOCKS5 and HTTP proxies.

Enables AI agents to control Chrome, Edge, Brave and other Chromium browsers through an extension and native messaging host, exposing a Claude-in-Chrome-compatible tool set for real clicks, typing, screenshots, accessibility-tree reading, page text, form filling, JavaScript execution, console and network inspection, file uploads and GIF recording. Agent sessions run in isolated tab groups with per-site permission prompts, activity logging and a global stop control.

Enables web crawling and content extraction from web pages, supporting multiple output formats like text, markdown, XML, and JSON, with robots.txt compliance and rate limiting.

An MCP-based rule parsing engine for creating book sources, supporting CSS selectors, JSONPath, regex, and text matching to extract and validate content from HTML, JSON, or text data.

Custom MCP server exposing an internet_search tool that fetches DuckDuckGo results, enabling AI agents to perform web searches and retrieve structured information.