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  • A
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    Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.
    Last updated
    MIT
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    🚀 Kill the Junior AI Era. 🤖 Level up your AI code to Principal standards. No more sloppy lines or junior mistakes. Automated ESLint ✨ TypeScript 🔧 Prettier 🎨 SonarQube 🛡️ Security 🔒 Complexity 📊 in seconds. High-stakes quality, forced to ship only the best. ⚡🏆 Goodbye, bad code. Hello, Principal Engineer. 🚀✨
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    MIT
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    Automatically enhances user prompts by applying expert-level prompt engineering techniques tailored to technical, creative, or analytical content types. It provides visual feedback on applied optimizations to ensure higher quality, structured, and more comprehensive AI responses.
    Last updated
    1
    MIT
  • A
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    A Node.js and TypeScript server project that provides a simple starter example with Express.js web server, supporting hot-reload, testing, and modular structure.
    Last updated
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    24
    ISC
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    Enables discovery and querying of available MCP servers from the official repository. Supports searching by name, description, features, categories, and provides random server suggestions for exploration.
    Last updated
    13
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    MIT
  • A
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    Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.
    Last updated
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    MIT
  • F
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    Intelligent knowledge base system that enables users to process documents in 25+ formats, perform semantic search and Q\&A through vector retrieval. Supports multiple AI models including OpenAI and DouBao with local processing capabilities.
    Last updated
    10
    5
  • A
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    Provides local Retrieval-Augmented Generation (RAG) capabilities using Ollama for embeddings and ChromaDB for vector storage. It enables users to ingest and perform semantic searches across PDF, Markdown, and TXT documents within MCP-compatible clients.
    Last updated
    4
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    MIT
  • A
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    MCP servers for quantitative trading: live trading signals, market data, NAV history, portfolio management with dual-track (AUTO/MANUAL) performance comparison. Supports both stdio and Streamable HTTP transport.
    Last updated
    3
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    A complete MCP server for Retrieval-Augmented Generation with file management and vector memory for agents. Supports multiple document formats (PDF, DOCX, TXT, MD, CSV, JSON) with semantic search using Hugging Face embeddings and ChromaDB for efficient vector storage.
    Last updated
    11
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    MIT