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maintenanceEnables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.
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"Slack Bot with RAG Document Retrieval and Automated Response System" matching MCP servers:
- Alicense-qualityDmaintenanceProvides 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.1MIT
- Flicense-qualityDmaintenanceEnables semantic search and question-answering over uploaded documents using vector embeddings and Google AI. Supports document organization with tags, section-aware queries, and hierarchical markdown structure preservation.
- Flicense-qualityCmaintenanceMCP server enabling Claude Desktop to answer questions from local Word and PDF documents by searching a vector index built from their contents.
- Alicense-qualityBmaintenanceEnables natural language search and analysis of uploaded PDF, CSV, and Excel documents using retrieval-augmented generation and MCP tools, providing contextual answers to user queries.MIT
- AlicenseAqualityBmaintenanceMinimal RAG-over-a-corpus MCP retrieval: search_knowledge returns cited chunks. Local embeddings.1MIT
- Alicense-qualityDmaintenanceA Retrieval Augmented Generation system that enables AI assistants to perform semantic searches and manage document indices for markdown files. It supports PostgreSQL with pgvector and integrates both Google Gemini and Ollama for intelligent embedding generation.1MIT
- Alicense-qualityDmaintenanceA vector search system that enables semantic retrieval of document chunks using MongoDB Atlas Vector Search and Voyage AI embeddings, allowing users to search documents by meaning rather than just keywords.2MIT
- Alicense-qualityDmaintenanceA deterministic MCP server for document processing and retrieval that enables AI agents to process, chunk, and vector-search documents without an LLM.MIT
- Alicense-qualityCmaintenanceAn MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.10MIT
- Alicense-qualityDmaintenanceEnables AI agents to search and retrieve relevant document content from existing embeddings stored in Supabase vector database. Provides semantic search capabilities to find document chunks based on similarity to query text without generating new embeddings.MIT
- Flicense-qualityDmaintenanceA Retrieval-Augmented Generation system that enables uploading, processing, and semantic search of PDF documents using vector embeddings and FAISS indexing for context-aware question answering.
- Flicense-qualityBmaintenanceLocal MCP server that provides a search_documents tool to query a RAG pipeline built with Ollama embeddings and ChromaDB, enabling Claude Desktop to retrieve relevant document chunks.
- AlicenseAqualityAmaintenanceLocal 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.13256MIT
- AlicenseAqualityAmaintenancePrivacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.93,271365MIT
- AlicenseAqualityBmaintenanceEnables 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.4AGPL 3.0
- AlicenseAqualityAmaintenanceRAG Vault lets your AI coding assistant search your private documents locally. Everything runs on your machine and your data stays private.92501MIT
- FlicenseAqualityDmaintenanceAn MCP server for semantic search and retrieval of indexed Slack messages stored in Qdrant using Cohere reranking via AWS Bedrock. It enables users to search through Slack history, retrieve full message threads, and access channel or user statistics through natural language.5
- AlicenseAqualityDmaintenanceProvides 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.4245MIT