The Apify MCP Server is a tool based on the Model Context Protocol (MCP) that allows AI assistants to extract data from websites such as social media, search engines, and e-commerce through thousands of ready-to-use crawlers, scrapers, and automation tools (Apify Actors). It supports OAuth and Skyfire proxy payment and can be integrated into MCP clients such as Claude and VS Code through HTTPS endpoints or local stdio.

An MCP service for web search without an API key based on multiple search engines, supporting structured result return and article content retrieval

An MCP server implementation integrating multiple search engines and web page scraping functions

ResearchMCP is a research tool that combines the Model Context Protocol (MCP) with multiple search engines, aiming to provide research capabilities similar to ChatGPT DeepResearch.

Uncover MCP is an MCP service implementation based on the uncover tool, used to quickly discover exposed hosts on the Internet, supporting multiple search engines and output formats.

The Kagi MCP Server is a tool integration service that provides search and summarization functions for Claude Desktop, supporting API calls to Kagi's search and summarization engines.

A search service implementation based on the MCP protocol, supporting multiple search engines and providing content acquisition capabilities for AI tools.

Open Deep Research MCP Server is an AI - driven deep research assistant that conducts iterative deep research by combining search engines, web scraping, and AI technology to generate comprehensive reports. It supports two usage methods: MCP protocol and CLI, and has functions such as reliability assessment, scope control, and automatic generation of follow - up questions.

An MCP server implementation for the DataForSEO API, supporting queries of various search engine data

MCP-GetWeb is a protocol server that provides web search and content extraction functions, supporting multiple search engines such as DuckDuckGo, Google, and Felo AI, and can crawl URL content, extract metadata, and convert it into Markdown format.

This project is a server based on the Model Context Protocol (MCP) that allows submitting URL indexing requests via the IndexNow protocol to help search engines discover and index website content faster.

This is an implementation of the scientific search MCP protocol designed for the Cursor editor, integrating multiple academic search engines (such as Google Scholar, PubMed, arXiv, etc.), supporting Semantic Scholar search through Tor, and providing functions such as PDF processing.

The Search Fusion MCP Server is a highly available multi-engine search aggregation service that provides intelligent failover, a unified API, and LLM-optimized content processing. It supports 7 search engines such as Google, Serper, and Jina AI, and has advanced functions such as concurrency control, connection pool management, and automatic proxy detection.