"FFmpeg" matching MCP servers:

Enables local media processing (video/audio) using FFmpeg and FFprobe, allowing frame extraction, audio conversion, and metadata retrieval through natural language.

Provides video and audio manipulation tools powered by FFmpeg, enabling AI assistants to perform media operations such as cutting, converting, and removing silence.

Enables LLMs to safely execute ffmpeg and ffprobe operations by passing arguments as arrays, avoiding shell injection, with support for probe, convert, trim, concat, thumbnail, watermark, speed, loudnorm, and batch processing.

Enables comprehensive video/audio processing, analysis, and streaming via natural language by exposing 40+ FFmpeg tools as MCP tools.

A job queue-based FFmpeg wrapper enabling AI assistants to perform video processing tasks such as trimming, format conversion, resolution change, and subtitle conversion through natural language.

Enables video and audio processing through FFmpeg, supporting format conversion, compression, trimming, audio extraction, frame extraction, video merging, and subtitle burning through natural language commands.

Provides 30+ FFmpeg video and audio editing tools via MCP, enabling AI assistants to perform operations like trimming, transcoding, overlays, and composition directly.

Enables comprehensive video and audio processing using FFmpeg, supporting tasks like metadata extraction, clipping, scaling, and adding transitions or overlays. It provides a high-performance interface for building media processing microservices via FastMCP.

An MCP server that exposes FFmpeg as structured tools for AI-agent-driven video editing, enabling operations like trimming, subtitling, and transcoding via natural language.

An MCP server that provides 17 FFmpeg-based tools for video and audio processing, including conversion, compression, and editing. It enables AI assistants to perform complex media tasks like extracting audio, adding watermarks, and merging videos using natural language.

Enables secure video and audio processing using FFmpeg commands in an isolated sandbox environment. Supports file management, Google Cloud Storage integration, and URL-based file transfers for AI-powered multimedia operations.

Enables image and video processing through FFmpeg, including compression, format conversion, resizing, and batch processing operations for common media formats.

Enables video processing tasks such as resizing, audio extraction, and metadata inspection using FFmpeg, with base64 input/output for stateless and portable operation.

A lightweight server that exposes FFmpeg's video processing capabilities to AI assistants through the Model Context Protocol (MCP), supporting operations like video format conversion, audio extraction, and adding watermarks.

Enables AI assistants to perform video and audio processing tasks such as format conversion, cutting, merging, and adding effects via FFmpeg, with hardware acceleration support.

A Node.js server that enables video manipulation through natural language requests, including resizing videos to different resolutions (360p to 1080p) and extracting audio in various formats (MP3, AAC, WAV, OGG).

An MCP server that masters audio with a professional signal chain using ffmpeg, enabling loudness analysis, vocal-over-beat mixing, full mastering to target LUFS, and Dolby codec export.

Loudness compliance verdicts against formal broadcast standards (EBU R128, ATSC A/85). Measures audio/video with ffmpeg and returns a pass/fail verdict with exact deltas and remediation parameters.

Enables LLMs to perform FFmpeg operations like clipping, merging, extracting audio, adding subtitles, and transcoding videos via a set of tools exposed as an MCP server.

Provides video manipulation via ffmpeg (frame extraction, format conversion, trimming, audio adjustments, filters, and subtitle handling) without requiring an external API key.