FFL

🚀 What's New in v3.9.1

Welcome to v3.9.1! This release is all about bringing FastFileLink into the era of AI Agents and further perfecting our Embedded Mode architecture.

🤖 AI Agent & MCP Integration

ffl is now fully equipped to work seamlessly as a tool for modern AI assistants!

• Agent Skills (SKILL.md): Added a dedicated skills/ffl/SKILL.md definition. This provides standard instructions so modern AI agents can natively understand how to use ffl to share and request files on your behalf.
• Official MCP Server: We've launched the official Model Context Protocol (MCP) implementation for FastFileLink! You can find it at nuwainfo/ffl-mcp.
  • It includes full support for media previews and has been thoroughly tested with Claude Code and Claude Cowork.
• ✨ Real-World AI Magic: With our MCP integration, you can now literally ask your AI assistant: "Hey Claude, take that massive video file on my computer and send it to my phone." Claude can utilize the Dispatch function to instantly generate an ffl link and deliver it to you!

🔌 Embedded Mode Enhancements

• Robust --upload Support: We've fine-tuned how the Server Upload (--upload) feature behaves when ffl is running as an embedded process. It now hooks perfectly into parent applications.
• The Perfect Code Sample: If you are a developer looking to integrate ffl into your own software, our new ffl-mcp repository serves as the perfect, production-ready reference. It is built entirely on top of ffl's Embedded Mode API!

📦 Which file should I download?

• If you want a single file that runs everywhere, across OSes? choose APE (ffl.com / fflo.com).
• If you want platform-optimized size/perf, choose a native build. 🙂
• On Linux and unsure about glibc (or on musl)? -> APE ffl.com is the safest choice.

ℹ️ On the first run of a native build, the app performs an internal extraction step (by pyapp), so startup is temporarily slower once.
The install scripts pre-warm this step; manual downloads will see the one-time delay.
APE builds (ffl.com / fflo.com) are single-file and do not have this first-run warmup.

Windows (native)

• x86_64 → ffl-v3.9.1-x86_64-windows.zip
  Unzip to get ffl.exe.

Linux (native)

We publish two glibc baselines. Pick the highest baseline that does not exceed your system glibc:

• glibc 2.39+ — smaller & faster

  • ffl-v3.9.1-manylinux_glibc2.39-x86_64-linux.tar.gz
  • Best for newer distros (e.g., Ubuntu 24).

• glibc 2.28+ — widest compatibility

  • ffl-v3.9.1-manylinux_glibc2.28-x86_64-linux.tar.gz
  • Works on older distros (e.g., Ubuntu 20); larger due to additional internal linking.

⚠️ If your system is musl-based (e.g., Alpine) or you’re unsure about glibc, prefer APE ffl.com.

macOS (native)

• Apple Silicon (arm64) → ffl-v3.9.1-aarch-darwin.tar.gz
• Intel (x86_64) → ffl-v3.9.1-x86_64-darwin.tar.gz

The archive unpacks to a single ffl binary.

🧰 APE (cross-platform single file, zero external deps)

• ffl.com — Single-file build that runs natively on Linux, macOS, Windows, FreeBSD, OpenBSD 7.3, NetBSD, BIOS, and Android (Termux).
• fflo.com — Alternative APE build that is exactly aligned with the open-source repo (no additional/proprietary addons).
  As a result, features that require closed-source components—such as upload to server (e.g., --upload)—are not available.

For a deeper comparison between native and APE, see the README’s notes.