Command Palette

Search for a command to run...

UnylyUnyly
Browse all

Media Toolkit Server

FreeNot checked

Local image processing MCP server providing background removal, stock media search, resize, format conversion, and collage creation.

GitHubEmbed

About

Local image processing MCP server providing background removal, stock media search, resize, format conversion, and collage creation.

README

Local Image Processing Toolkit for AI Assistants

License: MIT Python 3.11+ MCP Version 1.0.0

Background removal, stock media search, resize, format conversion, and collage creation.
All free and local — no cloud APIs needed (except optional Pexels search).
Works with Claude Code, Claude Desktop, Cursor, and any MCP-compatible client.

中文文档

Features

  • 5 toolsremove_background, search_stock_media, resize_image, convert_format, create_collage
  • Free & local — no paid cloud APIs required for image processing
  • AI background removal — powered by rembg (U2Net), runs entirely on your machine
  • Stock photo search — search millions of free photos via Pexels (free API key)
  • Smart resize — fit, fill, or center crop modes
  • Format conversion — PNG, JPG, WebP, SVG→PNG
  • Grid collage — arrange multiple images into customizable grids
  • Auto-save output images to disk with timestamps

Architecture

User Prompt → AI Assistant (Claude / Cursor) → MCP Server → Local Processing (Pillow / rembg)
                                                   ↓
                                             Save to disk + Display

How It Works

All image processing happens locally using Python libraries:

Tool Library Cloud API? Notes
remove_background rembg (U2Net) No Model downloads on first use (~170MB)
search_stock_media httpx Pexels API (free) Requires free API key
resize_image Pillow No Fit, fill, crop modes
convert_format Pillow No PNG/JPG/WebP/SVG→PNG
create_collage Pillow No Grid layout with spacing

Quick Start

1. Clone & install

git clone https://github.com/kevinten-ai/mcp-media-toolkit.git
cd mcp-media-toolkit
uv sync

Background removal is optional because its ML dependencies are much larger than the core server:

uv sync --extra background-removal

2. (Optional) Get a free Pexels API key — visit https://www.pexels.com/api/ → sign up → copy your key

3. Configure MCP

Claude Code (CLI)
# Without Pexels (all local tools work without any API key)
claude mcp add --transport stdio mcp-media-toolkit \
  -- uv --directory /path/to/mcp-media-toolkit run media-toolkit

# With Pexels stock photo search
claude mcp add --transport stdio mcp-media-toolkit \
  --env PEXELS_API_KEY=your_pexels_key \
  -- uv --directory /path/to/mcp-media-toolkit run media-toolkit
Claude Desktop / Cursor (JSON config)
{
  "mcpServers": {
    "mcp-media-toolkit": {
      "command": "uv",
      "args": ["--directory", "/path/to/mcp-media-toolkit", "run", "media-toolkit"],
      "env": {
        "PEXELS_API_KEY": "your_pexels_key"
      }
    }
  }
}

4. Use it — just ask your AI assistant:

"Remove the background from /path/to/photo.png"
"Search for stock photos of mountain landscapes"
"Resize this image to 1920x1080 using fill mode"
"Convert image.png to WebP format"
"Create a 3-column collage from these 6 images"

Output images are automatically saved to the output/ directory.

Tools

remove_background — AI Background Removal

Remove image backgrounds using the rembg library (U2Net model). Runs entirely locally.

remove_background(image_path="/path/to/photo.png")
remove_background(image_path="photo.jpg", output_path="/custom/output/result.png")
Parameter Required Description
image_path Yes Path to the input image
output_path No Custom output path (auto-generated if omitted)

Note: The first call downloads the U2Net model (~170MB). Subsequent calls are fast.

search_stock_media — Free Stock Photo Search

Search millions of free stock photos via the Pexels API.

search_stock_media(query="sunset beach")
search_stock_media(query="office workspace", count=10, orientation="landscape")
Parameter Required Description
query Yes Search terms (e.g. "sunset beach")
count No Number of results (default: 5, max: 80)
orientation No Filter: landscape, portrait, or square

Returns image URLs (original, large, medium) with photographer credits.

resize_image — Resize & Crop

Resize images with three modes:

resize_image(image_path="photo.png", width=1920, height=1080)
resize_image(image_path="photo.png", width=800, height=800, mode="fill")
resize_image(image_path="photo.png", width=500, height=500, mode="crop")
Parameter Required Description
image_path Yes Path to the input image
width Yes Target width in pixels
height Yes Target height in pixels
mode No fit (default, contain), fill (cover + crop), crop (center crop)
output_path No Custom output path

Modes explained:

  • fit — Resize to fit within the bounds, preserving aspect ratio. Result may be smaller than target.
  • fill — Resize to cover the bounds, then center crop. Result is exactly the target size.
  • crop — Center crop the original image to the target size (no resize).

convert_format — Format Conversion

Convert between PNG, JPG, WebP. Also supports SVG→PNG (requires cairosvg).

convert_format(image_path="photo.png", output_format="webp")
convert_format(image_path="icon.svg", output_format="png")
convert_format(image_path="photo.webp", output_format="jpg")
Parameter Required Description
image_path Yes Path to the input image
output_format Yes Target format: png, jpg, webp
output_path No Custom output path

Note: Converting RGBA images to JPEG automatically composites onto a white background.

create_collage — Grid Collage

Arrange multiple images into a grid layout.

create_collage(image_paths=["a.png", "b.png", "c.png", "d.png"])
create_collage(image_paths=["a.png", "b.png", "c.png"], columns=3, spacing=20)
Parameter Required Description
image_paths Yes List of image file paths
columns No Grid columns (default: 2)
spacing No Pixel spacing between images (default: 10)
output_path No Custom output path

Images are automatically resized to fit uniform cells within the grid.

Environment Variables

Variable Required Default Description
PEXELS_API_KEY No* Pexels API key for stock photo search. *Only required for search_stock_media tool. Free at pexels.com/api
IMAGE_OUTPUT_DIR No ./output Directory to save output images

Custom Output Directory

--env IMAGE_OUTPUT_DIR=/absolute/path/to/your/images

Images are saved with timestamps: rembg_20260331_143022.png, resize_20260331_143055.jpg, etc.

Troubleshooting

Common Errors

Error Root Cause Solution
PEXELS_API_KEY is required Missing API key for stock search Get a free key at pexels.com/api and set PEXELS_API_KEY
Image not found: /path/to/file File doesn't exist at given path Check the file path is correct and the file exists
rembg is not installed Optional dependency missing Run uv sync --extra background-removal

Background Removal

Issue Solution
First call is very slow (~30s) Normal — rembg downloads U2Net model (~170MB) on first use. Subsequent calls are fast.
Poor removal quality Try images with clear subject/background contrast. rembg works best with distinct foregrounds.
Out of memory Large images (>4000px) use significant RAM. Resize first with resize_image.

Format Conversion

Issue Solution
SVG conversion fails Install cairosvg: pip install cairosvg (requires system Cairo library)
JPEG output has black areas Transparent regions in source image. The tool auto-composites onto white — check input has correct alpha.
WebP not supported Ensure Pillow is built with WebP support (default in most installations)

Pexels API

Issue Solution
429 Too Many Requests Free tier allows 200 requests/hour and 20,000/month. Wait or upgrade.
No results Try broader search terms. Pexels search works best with English keywords.

Prerequisites

  • Python 3.11+
  • uv — install with curl -LsSf https://astral.sh/uv/install.sh | sh

Local Development

git clone https://github.com/kevinten-ai/mcp-media-toolkit.git
cd mcp-media-toolkit

# Install dependencies
uv sync

# Run the server directly
uv run media-toolkit

Debug with MCP Inspector

npx @modelcontextprotocol/inspector uv --directory /path/to/mcp-media-toolkit run media-toolkit

Related Projects

  • mcp-image-gen — AI image generation via Google Gemini and Imagen
  • mcp-video-gen — Multi-provider AI video generation MCP server
  • mcp-3d-gen — AI 3D model generation MCP server

License

MIT — see LICENSE for details.

from github.com/kevinten-ai/mcp-media-toolkit

Install Media Toolkit Server in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install media-toolkit-mcp-server

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add media-toolkit-mcp-server -- uvx --from git+https://github.com/kevinten-ai/mcp-media-toolkit mcp-media-toolkit

FAQ

Is Media Toolkit Server MCP free?

Yes, Media Toolkit Server MCP is free — one-click install via Unyly at no cost.

Does Media Toolkit Server need an API key?

No, Media Toolkit Server runs without API keys or environment variables.

Is Media Toolkit Server hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Media Toolkit Server in Claude Desktop, Claude Code or Cursor?

Open Media Toolkit Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

Related MCPs

Compare Media Toolkit Server with

Not sure what to pick?

Find your stack in 60 seconds

Author?

Embed badge for your README

Browse similar

All media MCPs