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"An MCP to access OpenAI's RAG system via API" matching MCP servers:

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    MCP 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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    An MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.
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    10
    MIT
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    An agentic AI system that orchestrates multiple specialized AI tools to perform business analytics and knowledge retrieval, allowing users to analyze data and access business information through natural language queries.
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    3
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    Hybrid RAG over Claude Code and Hermes session history via MCP tools for search, ingest, and context injection.
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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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    A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.
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    3
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    MIT
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
    Last updated
    3
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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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    4
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    A local-first document retrieval MCP server that enables AI coding tools like Codex to search private local documents via semantic search and keyword boost, supporting ingestion of PDF, DOCX, TXT, Markdown, and HTML files.
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    7
    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.
    Last updated
    4
    AGPL 3.0
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    A fully modular RAG system with MCP protocol integration, enabling hybrid retrieval, multimodal support, and dual-mode transport for connecting to AI assistants like GitHub Copilot and Claude Desktop.
    Last updated
    5
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    MIT
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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