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    An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.
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    An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.
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    Local RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.
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    256
    MIT
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    A RAG-based knowledge base system supporting document processing, semantic search, and intelligent Q\&A with multiple AI model integrations.
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    MCP server that integrates Apache Ranger authorization with RAG, enforcing Ranger policies to control access to knowledge bases before forwarding queries to RAG Studio.
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    Apache 2.0
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    Enables indexing local documents (PDF, Markdown, text, code) into a knowledge base and querying them via semantic search using local embeddings, all running privately on your machine.
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    Enables semantic search and question answering over a knowledge base using hybrid retrieval and grounded answers, all running offline with no API keys.
    4
    MIT
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    Enables ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.
    4
    AGPL 3.0
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    A Model Context Protocol (MCP) server that provides a local-first RAG engine for your markdown documents. It uses a file-based Milvus vector database to index your notes, enabling LLMs to perform semantic search and retrieve relevant content from your local files.
    3
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    Apache 2.0
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    A local-first document retrieval engine that mounts as an MCP tool for agents to index files, search for relevant passages, and let the agent's own LLM answer.
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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.
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    MIT
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    Enables storing and retrieving text passages based on semantic meaning using local embeddings (Ollama) and vector storage (ChromaDB), allowing conversational memorization and retrieval of information.
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    MIT
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    A server that implements Retrieval-Augmented Generation using GroundX and OpenAI, enabling semantic search and document retrieval with Modern Context Processing for enhanced context handling.
    3
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    A local MCP server that gives Claude Code web search capabilities using DuckDuckGo, enabling discovery of URLs from natural language queries.
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    An MCP server that allows coding agents to search the Swift Package Index and retrieve GitHub READMEs without requiring an API key. It features comprehensive search filters for stars, platforms, and licenses, providing token-efficient responses optimized for LLM comprehension.
    3
    MIT
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    MCP server that integrates with LM Studio to provide a search_notes tool, allowing the chat model to retrieve and answer from a local Obsidian vault.
    1
    MIT