Show HN: Giving Claude Code "hands" to deliver local files (P2P, No Cloud) (github.com)

A new project titled "ffl-mcp" has been introduced, enabling the Claude AI model to share local files directly through peer-to-peer (P2P) links without relying on cloud storage. This minimalistic MCP (Multi-Client Protocol) server works by transforming any file or folder into an HTTPS link via the FastFileLink (ffl) service. The key feature is that no file contents are sent to the AI model, ensuring data privacy while allowing for collaborative tasks, such as debugging. In a demonstration, one Claude instance shared a local environment complete with a database and logs with another instance, exemplifying its practical use. This development is significant for the AI/ML community because it addresses privacy concerns associated with cloud-based file sharing while enhancing collaborative workflows. By utilizing end-to-end encryption (E2EE) and enabling P2P transfers, ffl-mcp ensures secure and efficient file sharing between local devices. The implementation details, such as session management functions and local configurations, provide users with a flexible tool for managing and transferring data securely within their environments, paving the way for more robust applications in machine learning and collaborative development.