Open Search

Aggregates multiple search engines, academic databases, and content sources with intelligent load balancing and failover mechanisms to provide web search, research capabilities, and PDF processing with OCR support as a free alternative to paid search APIs.

This MCP server provides AI assistants with comprehensive web search, academic research, and content extraction capabilities through a free, open-source alternative to paid search APIs, built by Open Search MCP Contributors using TypeScript with dual MCP/HTTP API operation modes. The implementation aggregates multiple search engines (DuckDuckGo, Google, Bing), academic databases (arXiv, PubMed, IEEE), social platforms (Reddit, GitHub), and news sources with intelligent load balancing, health monitoring, and failover mechanisms across distributed Searx clusters. Features advanced PDF processing with OCR support, AI-powered query optimization through local Ollama models (Llama 3.2, Qwen 2.5), semantic search with vector databases, and multi-platform integration for Claude Desktop, Cursor, VSCode, and Windsurf, serving researchers needing comprehensive literature review capabilities, developers requiring real-time technical information gathering, and teams building knowledge-intensive applications without relying on expensive third-party search APIs.