FFmpeg MCP Server

The FFmpeg-MCP server transforms the power of FFmpeg’s command‑line video processing into a conversational tool that AI assistants can invoke directly. By exposing a set of high‑level video manipulation commands as MCP tools, developers can ask an assistant to locate, analyze, edit, or play media files on a local machine without writing shell scripts or dealing with FFmpeg’s complex syntax. This eliminates the friction of integrating video workflows into chat‑based interfaces, enabling rapid prototyping and production pipelines that respond to natural language queries.

At its core, the server offers a suite of video‑centric capabilities that cover most common editing tasks:

• File discovery () allows the assistant to search a directory tree for a given file name, supporting partial matches and recursive traversal.
• Metadata extraction () returns duration, frame rate, codec, and resolution, letting the assistant make informed decisions about downstream processing.
• Trimming () cuts a segment from an existing file by start and end times or duration, producing a new clip path.
• Concatenation () stitches together multiple videos, automatically selecting a fast “quick‑mode” merge when all inputs share compatible codecs and dimensions.
• Playback () launches for immediate preview, supporting loop counts and speed adjustments.
• Overlay () layers one video atop another with fine‑grained positioning, useful for picture‑in‑picture or watermarking.
• Scaling () resizes content while preserving aspect ratio, outputting a new file.
• Frame extraction () pulls individual frames into an image directory, supporting PNG, JPG, or WEBP formats and configurable frame rates.

These tools are intentionally straightforward: each takes a small set of parameters, returns a clear path or metadata object, and relies on FFmpeg’s proven performance. For developers, this means they can embed complex media workflows into AI‑driven applications—such as automated video summarization, dynamic content creation for social media, or responsive multimedia storytelling—without maintaining a separate FFmpeg wrapper library.

Integration into AI pipelines is seamless. An MCP client can request by simply stating, “Trim the first 30 seconds of intro.mp4,” and receive a path to the resulting clip. The assistant can then chain that result into or , building multi‑step editing sequences entirely through dialogue. Because the server runs locally, latency is minimal and privacy concerns are mitigated; no media files leave the host machine.

A standout advantage of FFmpeg-MCP is its native handling of diverse media formats. From MP4 and MKV to AVI, MOV, and 3GP, the server can play or edit any format supported by FFmpeg. The automatic quick‑mode concatenation reduces processing time for large projects, and the overlay tool’s precise offset parameters enable creative compositing without manual keyframe work. These features make FFmpeg-MCP an indispensable bridge between human intent expressed in natural language and the exacting demands of professional video production.