Showing 4 open source projects for "mount"

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  • 1
    FastAPI-MCP

    FastAPI-MCP

    Expose your FastAPI endpoints as Model Context Protocol (MCP) tools

    ...The server speaks directly to your app over its ASGI interface, avoiding extra HTTP hops between the MCP layer and your API, which reduces latency and simplifies deployment. A tiny bootstrap is enough to stand up an MCP server and, if desired, mount an HTTP transport for remote clients. The docs emphasize a FastAPI-first workflow: keep your schemas, reuse your middleware, and surface endpoints to agents without rewriting controllers. The project is active, with examples and a dedicated site that shows getting started, security, and transport options.
    Downloads: 8 This Week
    Last Update:
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  • 2
    e-Dokyumento

    e-Dokyumento

    e-Dokyumento is web-based Document Management System (DMS)

    ...Download: https://sourceforge.net/projects/e-dokyumento/files/Releases/e-DokyuV3.iso/download 2. Boot and login with: "root" and "admin@123" 3. Create 2 partitions: SWAP and / mount 4. Login and move "/opt/drive" folder to root: "mv /opt/drive /" # Install on Ubuntu: https://sourceforge.net/projects/e-dokyumento/files/Install%20e-Dokyumento%20on%20Ubuntu%20Linux.pdf/download
    Downloads: 0 This Week
    Last Update:
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  • 3
    Photonix Photo Manager

    Photonix Photo Manager

    A modern, web-based photo management server

    ...You can move some photos into the folder data/photos and they should get detected and imported immediately. Once you have finished trying out the system you can edit the volume in the docker-compose.yml file where it says ./data/photos to mount wherever you usually keep photos. System database, thumbnails and other cache data is stored separately from the photos so shouldn't pollute the area. You are responsible for keeping your own backups in case of error.
    Downloads: 4 This Week
    Last Update:
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  • 4
    Aquila DB

    Aquila DB

    An easy to use Neural Search Engine

    Aquila DB is a Neural search engine. In other words, it is a database to index Latent Vectors generated by ML models along with JSON Metadata to perform k-NN retrieval. It is dead simple to set up, language-agnostic, and drop in addition to your Machine Learning Applications. Aquila DB, as of current features is a ready solution for Machine Learning engineers and Data scientists to build Neural Information Retrieval applications out of the box with minimal dependencies.
    Downloads: 0 This Week
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