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    Read-only MCP server exposing Desktop Mate directory listings, official links, and FAQ to AI clients like Claude Desktop.
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    MIT
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    Enables local document search and reading across formats like docx, pdf, md, and more, providing tools for listing, searching, and reading documents.
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    Enables Claude to query a locally imported collection of PDF, TXT, and MD files via SQLite FTS5 full-text search (including Chinese), and to browse notebooks, source files, and individual passages. Every search result carries traceable citations such as filename, page number, line number, or timestamp.
    MIT
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    Enables LLM clients to query local markdown engineering documentation by indexing files into ChromaDB with Ollama embeddings and exposing a search_internal_docs tool over stdio, all offline and privacy-first.
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    The Orderly Network MCP server gives AI assistants direct access to Orderly documentation, SDK patterns, API references, workflows, and contract addresses through a single MCP integration. It helps developers build trading UIs and integrations faster by making Orderly-specific guidance and code examples instantly queryable.
    308 npm
    9
    MIT
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    Read-only MCP server for a local-first supply chain knowledge base, enabling knowledge search with source evidence, internal system troubleshooting, vendor documentation fallback, vessel tracking, and work handoff preparation.
    MIT
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    Provides AI agents with access to Zero Network documentation, SDK integration guides, and utility tools for crypto-based payments. It enables developers to implement x402 paywalls and per-tool MCP pricing while offering real-time cost estimations and revenue calculations.
    14
    MIT
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    Local MCP server for Kiubi graphic theme integration, exposing tools for documentation, theme introspection, and static file validation to AI agents like Claude and Cursor.
    14 npm
    1
    ISC
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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
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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
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    Enables semantic search and interaction with Fuel Network documentation and Sway Language resources within AI-powered development environments. It provides high-quality technical context using a local vector database to assist with smart contract development and FuelVM queries.
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