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  • A
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    quality
    C
    maintenance
    Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.
    MIT
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    quality
    C
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    Enables AI models to securely and structurally assimilate experiences, thoughts, and reasoning processes across different AI systems, fostering intellectual collaboration and evolutionary dialogue.
    17
    MIT
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    C
    maintenance
    ai-detect is a free AI text detector that runs entirely on your own hardware. It scores writing sentence by sentence using desklib/ai-text-detector-v1.01, a 304-million-parameter DeBERTa-v3-large model that ranks first on the RAID detection benchmark. No API key, no per-word pricing and no upload: after a one-off 1.7 GB model download it just works offline. by Houtini
    3
    MIT
  • A
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    D
    maintenance
    Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.
    15
    34
    MIT
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    B
    maintenance
    Enables chat-driven audio analysis and enhancement using local Claude, including denoising, EQ, compression, and loudness normalization, with an A/B viewer for synchronized comparison.
    1
    MIT
  • A
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    quality
    D
    maintenance
    Enables AI assistants to control Blender 3D modeling and rendering through natural language commands via the Model Context Protocol.
    MIT
  • F
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    quality
    D
    maintenance
    Enables 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.
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    Enables AI agents to perform CRM operations like creating contacts, managing deals, and updating leads through natural language using the Model Context Protocol.
    4
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  • A
    license
    A
    quality
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    maintenance
    An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.
    7
    3
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