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Adityaaery20/media-mcp

by Various

๐Ÿ ๐Ÿ  ๐ŸŽ ๐ŸชŸ ๐Ÿง - Local image and video processing MCP server with 13 tools for resize, convert, compress, crop, thumbnail, metadata extraction, rotate, flip, filters, and ffmpeg-ba

A

MCP

Adityaaery20/media-mcp

Added 1 June 2026

Overview

A local MCP server for image and video processing that exposes 13 tools for common operations like resize, convert, compress, crop, thumbnail generation, metadata extraction, rotate, flip, filters, and ffmpeg-based tasks. It runs locally and communicates via the Model Context Protocol, enabling AI agents to manipulate media files directly.

Best for

Best for
Developers building local AI agent pipelines that need basic image and video manipulation

Use cases

  • Automating batch image resizing and format conversion for web assets
  • Extracting metadata from media files for cataloging or analysis
  • Applying filters or transformations to images and videos via AI agent workflows

Notes

A local MCP server for image and video processing that exposes 13 tools for common operations like resize, convert, compress, crop, thumbnail generation, metadata extraction, rotate, flip, filters, and ffmpeg-based tasks. It runs locally and communicates via the Model Context Protocol, enabling AI agents to manipulate media files directly.

3 stars on GitHub. Last updated 2026-03-19. Licensed MIT.

Use cases

  • Automating batch image resizing and format conversion for web assets
  • Extracting metadata from media files for cataloging or analysis
  • Applying filters or transformations to images and videos via AI agent workflows

Pros

  • Runs locally with no external API dependencies
  • Covers a broad set of common media operations in one tool
  • Integrates with MCP-compatible AI assistants for automated workflows

Cons

  • Limited to 13 tools, may lack advanced or niche operations
  • Requires Python environment and ffmpeg installation
  • Small community and low star count suggest limited support and updates

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Runs locally with no external API dependencies
  • Covers a broad set of common media operations in one tool
  • Integrates with MCP-compatible AI assistants for automated workflows

Cons

  • Limited to 13 tools, may lack advanced or niche operations
  • Requires Python environment and ffmpeg installation
  • Small community and low star count suggest limited support and updates