AI-Search-Hub by minsight-ai-info is an open-source AI Skill designed to aggregate the native search and web extraction capabilities of leading AI platforms like Gemini, Grok, Doubao, Yuanbao, and Kimi. It establishes an efficient, reusable information hub that resolves common data acquisition challenges such as crawler maintenance, platform anti-bot measures, and data cleaning. Users can perform "one query, whole-domain searches" to freely and efficiently gather diverse information, including tech trends, industry sentiment, and data from hard-to-reach sources like WeChat Official Accounts and Douyin. This hub empowers Agents and workflows to leverage major AI platforms' robust understanding and processing power, automating information collection, cleaning, and organization into structured outputs, significantly enhancing data acquisition efficiency and quality.
graphify is a multimodal knowledge graph construction tool meticulously designed for AI Agents, deeply integrated within the Claude Code environment. It transforms diverse information sources—including code, documents, papers, images, and video links—into queryable, structured knowledge graphs, leveraging Claude Vision to intelligently extract core concepts and relationships. This tool dramatically enhances information retrieval efficiency, saving up to 71.5x tokens per query, and ensures cross-session graph persistence. With intelligent insights and automated synchronization, graphify empowers developers and researchers with efficient intelligent assistance and advanced knowledge management.
GitNexus is an innovative zero-server code intelligence engine designed to significantly enhance AI agents' code understanding and analysis capabilities. It indexes any codebase into a detailed knowledge graph, exposing deep structural information such as dependencies, call chains, module clusters, and execution flows. Leveraging its core local CLI and Multi-Protocol Communication (MCP) framework, GitNexus provides mainstream AI agents like Cursor, Claude Code, and Codex with an unparalleled architectural view and rich context, boosting their reliability and accuracy in code exploration, debugging, refactoring, and generation tasks. A convenient browser Web UI is also available for quick exploration, alongside enterprise SaaS and self-hosted deployment options.
code-review-graph is an AI-assisted code review tool that builds a structural map of code using Tree-sitter and incrementally tracks changes to provide precise context to AI assistants via the Model Context Protocol (MCP). This approach significantly reduces token consumption by enabling AI models to read only the minimal set of files relevant to a change, rather than the entire codebase. It aims to solve the token waste problem in large repositories and monorepos, improving the efficiency and quality of AI code reviews.