Kindly Web Search

关于

Traditional web search tools often fail AI coding assistants by providing only snippets and links, forcing extra scraping calls that yield incomplete or noisy data. Kindly Web Search addresses this by delivering a holistic solution tailored for AI coding tools like Claude Code, Codex, and GitHub Copilot. It integrates directly with specialized APIs for platforms like StackExchange, GitHub, arXiv, and Wikipedia to retrieve entire conversations—including questions, answers, comments, and metadata—in a single, LLM-optimized format. For general web pages, it uses a headless browser for real-time parsing, ensuring immediate access to all useful content without the need for subsequent scraping. This design significantly enhances the efficiency and effectiveness of AI assistants in solving complex technical problems.

主要功能

• Returns full conversations (questions, answers, comments, reactions, metadata) in a single API call.
• Parses any webpage in real-time using a headless browser for comprehensive, up-to-date content.
• Delivers all useful content to the LLM immediately, eliminating the need for secondary scraping calls.
• Supports multiple search providers (Serper and Tavily) with intelligent fallback capabilities.
• 2 GitHub stars
• Integrates directly with APIs for StackExchange, GitHub Issues, arXiv, and Wikipedia for structured content.

使用案例

• Streamlining the research process for developers by providing full conversational context from platforms like StackOverflow and GitHub.
• Reducing the reliance on multiple, specialized MCP servers (generic search, StackOverflow, web scraping) by consolidating functionality.
• Enhancing AI coding assistants to retrieve comprehensive solutions for complex technical issues and debugging.