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    LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.
    21
    1
    MIT
  • F
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    quality
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    Enables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.
  • A
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    Provides AI agents with comprehensive document parsing capabilities including PDF text extraction, OCR, HTML-to-markdown conversion, table extraction, and summarization, optimized for agent workflows.
    61
    MIT
  • F
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    Exposes an internal engineering knowledge base to AI assistants, allowing users to search and retrieve standards, runbooks, and architecture decisions. It supports RAG-enhanced search, document scraping, and specialized prompts for incident investigation and code reviews.
    5
  • A
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    quality
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    A local document evidence layer for MCP clients that ingests documents (PDF, Office, images) with optional OCR, indexes them in SQLite FTS, and provides retrieval tools with source coordinates.
    7
    MIT
  • A
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    quality
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    Enables AI agents to search, deep-read, and build knowledge bases from Markdown, PDF, DOCX, and PPTX documents via MCP tools for retrieval, document navigation, and ingestion.
    44
    613
    MIT
  • A
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    A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.
    MIT
  • A
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    Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.
    MIT
  • A
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    A 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.
    2
    MIT
  • A
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    Enables real-time indexing and semantic search of local documents (PDF, Word, text, Markdown, RTF) using vector embeddings and local LLMs. Monitors folders for changes and provides natural language search capabilities through Claude Desktop integration.
    22
    MIT
  • A
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    An MCP server that uses the Docling toolkit to convert various document formats, including PDFs, Office files, images, and audio, into clean Markdown for AI processing. It supports multiple processing pipelines like VLM and ASR with intelligent auto-detection and job queue management.
    2
    MIT
  • A
    license
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    quality
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    maintenance
    Federated, local-first search for AI agents: one query fans across transcripts, files, a knowledge graph, a vector store, the live web, and YouTube, fused by trust-weighted RRF into one ranked answer. Five modes (grep/lexical/semantic/hybrid/rerank), runs entirely on your machine over MCP.
    6
    29
    Apache 2.0
  • A
    license
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    quality
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    maintenance
    Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.
    9
    2
    1
    MIT
  • A
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    quality
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    maintenance
    MCP search and evidence tool for AI agents. Rewrites queries, zooms into source domains, and returns sourced answers with metrics.
    4
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    MIT