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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:
- Flicense-qualityBmaintenanceMCP server for a modular RAG system that enables natural language question answering over enterprise documents with intent-aware routing, adaptive retrieval, and citation-backed responses.
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- AlicenseAqualityBmaintenanceA black-box flight recorder for RAG retrieval inside MCP agents. Logs what chunks the model saw, scores, sources, and rankings - so you can audit, replay, and diff retrieval runs after the fact.4152MIT
- Flicense-qualityDmaintenanceEnables AI applications to access and contextualize organizational knowledge sources including GitHub repositories and internal documentation through standardized MCP protocol integration. Features OAuth 2.1 authentication, vector-based semantic search, and optimized context chunking for enterprise development workflows.
- Flicense-qualityCmaintenanceMCP server enabling Claude Desktop to answer questions from local Word and PDF documents by searching a vector index built from their contents.
Watsonx.data Document Libraryofficial
Alicense-qualityCmaintenanceBridges AI agents with watsonx.data document libraries, enabling natural language queries and intelligent retrieval from document libraries.4Apache 2.0- 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
- 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-qualityDmaintenanceThe MCP server provides tools for entity extraction, query refinement, and relevance checking to enhance RAG applications by integrating with OpenAI and Gemini.
- FlicenseBqualityDmaintenanceA RAG-based knowledge base system supporting document processing, semantic search, and intelligent Q\&A with multiple AI model integrations.1
- Alicense-qualityCmaintenanceProvides AI agents with comprehensive document parsing capabilities including PDF text extraction, OCR, HTML-to-markdown conversion, table extraction, and summarization, optimized for agent workflows.101MIT
- 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-qualityBmaintenanceAn evaluation harness that probes MCP-based retrieval servers for calibration, relevance, coverage, citation integrity, and more, also exposing the probes as MCP tools for assistants and CI agents.MIT
- 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-qualityDmaintenanceEnables integration with financial transaction data through REST APIs, PostgreSQL databases, and document storage systems. Demonstrates agentic AI capabilities by connecting to Alpha Vantage API and managing financial data through natural language interactions.