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    Jinni is a tool to efficiently provide Large Language Models the context of your projects. It gives a consolidated view of relevant project files complete with metadata, overcoming the limitations and inefficiencies of reading files one by one. The philosophy behind this tool is that LLM context wi
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    Apache 2.0
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    Enables AI agents to discover and execute solar energy domain tools such as solar cell simulation, perovskite parameter/bandgap/aging prediction, RAG knowledge retrieval, and curve/table generation through MCP.
    MIT
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    Provides a find_solution tool that retrieves verified, compressed coding solutions from a curated library and injects them into AI coding agents like Claude Code and Cursor via MCP, improving problem-solving success rates by up to 50%.
    MIT
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    A Model Context Protocol server that provides AI-grounded Bing search capabilities using the Azure AI Project Client. It enables intelligent web searches with automated citation tracking and URL extraction for seamless AI integration.
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