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MCP FFmpeg Helper

by sworddut

MCP FFmpeg Helper is a lightweight server that exposes FFmpeg's powerful capabilities to AI assistants through the Model Context Protocol (MCP). It provides various video processing functionalities.

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What is MCP FFmpeg Helper?

MCP FFmpeg Helper is a server that acts as a bridge between AI assistants and FFmpeg, allowing AI to perform video and audio manipulation tasks.

How to use MCP FFmpeg Helper?

The server is configured via MCP configuration files. It can be used with Windsurf or other MCP-compatible applications by adding the appropriate configuration. Once configured, you can interact with it through the AI assistant using natural language commands to perform video processing tasks.

Key features of MCP FFmpeg Helper

  • Get video file details

  • Convert video formats

  • Extract audio from video

  • Create video from image sequences

  • Trim video

  • Add watermark to video

  • Trim audio files

  • Extract frames from video

Use cases of MCP FFmpeg Helper

  • Automated video editing workflows

  • AI-powered video content creation

  • Programmatic video format conversion

  • Integration with AI assistants for media manipulation

FAQ from MCP FFmpeg Helper

How do I ensure FFmpeg is correctly installed?

Verify that FFmpeg is installed and accessible via the command line by running ffmpeg -version.

What if I encounter file path issues?

Double-check file paths, especially when using backslashes in Windows. Ensure the application has the necessary permissions to access the files and directories.

How can I pass additional FFmpeg options?

Use the options or extraOptions parameters in the function calls to pass additional command-line options to FFmpeg.

What image format and quality should I use for frame extraction?

For best quality, use the PNG format and set a high quality value (95-99).

How do I add new FFmpeg functionalities?

Modify src/tools/definitions.ts to add the new tool definition and src/tools/handlers.ts to add the corresponding implementation, then rebuild the project using npm run build.