Skip to main content

MCP Server for Stability AI image generation on AWS Bedrock

Project description

mcp-server-bedrock-image

CI Python 3.12+ License: MIT MCP

An MCP (Model Context Protocol) server that gives AI agents the ability to generate, edit, and manipulate images using Stability AI models on AWS Bedrock.

Connect it to Claude Code, Cursor, Windsurf, VS Code, or any MCP-compatible client — then ask your AI to generate images, remove backgrounds, transfer styles, upscale, and more.

Tools

Tool What it does Model
generate_image High-quality text-to-image generation Stable Image Ultra
generate_image_core Faster, lower-cost generation Stable Image Core
remove_background Remove image background Stability Remove Background v1
style_transfer Apply style from a reference image Stability Style Transfer v1
search_and_recolor Recolor specific elements by description Stability Search & Recolor v1
outpaint Extend image in any direction Stability Outpaint v1
search_and_replace Find and replace objects in an image Stability Search & Replace v1
upscale_fast 4x resolution upscale Stability Fast Upscale v1
upscale_creative Creative upscale up to 4K Stability Creative Upscale v1
compose_branded Composition-aware logo overlay Local (Pillow — no Bedrock call)

Quickstart

Prerequisites

Install & run

# Run directly (no install needed)
uvx mcp-server-bedrock-image

# Or install globally
uv tool install mcp-server-bedrock-image

Authentication

Two auth modes are supported:

boto3 mode (default) — Uses standard AWS credential chain (env vars, ~/.aws/credentials, IAM roles, STS):

export AWS_REGION=us-west-2

Bearer token mode — Uses Bedrock API keys (no AWS CLI setup needed):

export BEDROCK_AUTH_MODE=bearer
export AWS_BEARER_TOKEN_BEDROCK=your-api-key-here
export AWS_REGION=us-west-2

Client Configuration

Claude Code

Add to .claude/settings.json:

{
  "mcpServers": {
    "bedrock-image": {
      "command": "uvx",
      "args": ["mcp-server-bedrock-image"],
      "env": {
        "AWS_REGION": "us-west-2",
        "IMAGE_STORAGE_DIRECTORY": ".content-workspace/images"
      }
    }
  }
}

For bearer token auth, add "BEDROCK_AUTH_MODE": "bearer" and "AWS_BEARER_TOKEN_BEDROCK": "your-api-key" to the env block.

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "bedrock-image": {
      "command": "uvx",
      "args": ["mcp-server-bedrock-image"],
      "env": {
        "AWS_REGION": "us-west-2"
      }
    }
  }
}
VS Code

Add to .vscode/mcp.json:

{
  "servers": {
    "bedrock-image": {
      "command": "uvx",
      "args": ["mcp-server-bedrock-image"],
      "env": {
        "AWS_REGION": "us-west-2"
      }
    }
  }
}
Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "bedrock-image": {
      "command": "uvx",
      "args": ["mcp-server-bedrock-image"],
      "env": {
        "AWS_REGION": "us-west-2"
      }
    }
  }
}

Environment Variables

Variable Default Description
AWS_REGION us-west-2 AWS region for Bedrock
BEDROCK_AUTH_MODE boto3 Auth mode: boto3 or bearer
AWS_BEARER_TOKEN_BEDROCK Bedrock API key (bearer mode only)
BEDROCK_ENDPOINT Auto from region Override Bedrock runtime endpoint
IMAGE_STORAGE_DIRECTORY /tmp/mcp-server-bedrock-image Where to save generated images
SAVE_METADATA true Save JSON metadata alongside images

See .env.example for a template.

Usage Examples

Once connected, ask your AI agent naturally:

"Generate a hero image of a modern hotel lobby with warm lighting in 16:9"

"Remove the background from this product photo"

"Apply the style of this watercolor painting to the room photo"

"Add our logo to the generated image in the least busy corner"

Or call tools directly:

# Generate
generate_image(prompt="Modern hotel lobby with warm lighting", aspect_ratio="16:9")

# Edit
remove_background(image_path="/path/to/photo.png")
style_transfer(prompt="Watercolor style", image_path="room.png", style_image_path="ref.png")
search_and_replace(image_path="scene.png", prompt="red chair", search_prompt="blue chair")
outpaint(image_path="photo.png", prompt="extend the garden", right=200, bottom=100)

# Upscale
upscale_fast(image_path="/path/to/small.png")
upscale_creative(image_path="photo.png", prompt="enhance details, sharp textures")

# Brand
compose_branded(image_path="hero.png", logo_path="logo.png", output_path="branded.png")

How compose_branded works

The composition-aware branding tool doesn't use Bedrock — it runs locally with Pillow. It divides the image into a 3x3 grid, scores each quadrant by visual complexity (standard deviation of grayscale values), and places the logo in the least complex region. It also auto-selects between light and dark logo variants based on the background brightness.

Architecture

src/mcp_server_bedrock_image/
├── server.py          # FastMCP server — registers all 10 tools
├── config.py          # Environment variables and model IDs
├── bedrock_client.py  # Dual-auth Bedrock client (boto3 + bearer)
├── image_utils.py     # Image save and metadata utilities
└── tools/
    ├── generate.py    # Text-to-image generation
    ├── edit.py        # Background removal, style transfer, recolor, outpaint, search-replace
    ├── upscale.py     # Fast and creative upscaling
    └── compose.py     # Composition-aware logo placement

Development

# Clone and install
git clone https://github.com/Yaksh36/mcp-server-bedrock-image.git
cd mcp-server-bedrock-image
uv sync --all-extras --dev

# Run tests
uv run pytest -v

# Lint and format
uv run ruff check src/ tests/
uv run ruff format src/ tests/

Contributing

Contributions are welcome. Please:

  1. Fork the repo and create a feature branch
  2. Add tests for new functionality
  3. Ensure uv run pytest -v and uv run ruff check src/ tests/ pass
  4. Open a pull request

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mcp_server_bedrock_image-0.1.0.tar.gz (67.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mcp_server_bedrock_image-0.1.0-py3-none-any.whl (13.7 kB view details)

Uploaded Python 3

File details

Details for the file mcp_server_bedrock_image-0.1.0.tar.gz.

File metadata

  • Download URL: mcp_server_bedrock_image-0.1.0.tar.gz
  • Upload date:
  • Size: 67.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for mcp_server_bedrock_image-0.1.0.tar.gz
Algorithm Hash digest
SHA256 34e021053a1472d34192e99481aca6894e4525b1bc5868ba53fca794d5ffc4a2
MD5 a373d34097caf0405ec7308248667e9a
BLAKE2b-256 b13b74cf6ae426b28752511aeeb5386bd33197b20a86b29987142f2f9896a5c5

See more details on using hashes here.

Provenance

The following attestation bundles were made for mcp_server_bedrock_image-0.1.0.tar.gz:

Publisher: publish.yml on Yaksh36/mcp-server-bedrock-image

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mcp_server_bedrock_image-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for mcp_server_bedrock_image-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a8355df53ee6a072ba68b83f22301fe4fc1d1b86631181ab93dfc7ff17b4b41c
MD5 45589b643b7ab5405545c2de0791eb21
BLAKE2b-256 ad1c6aa9b1e1b798e231e87a87d61554db69d7d15c609c65f100600c140d112e

See more details on using hashes here.

Provenance

The following attestation bundles were made for mcp_server_bedrock_image-0.1.0-py3-none-any.whl:

Publisher: publish.yml on Yaksh36/mcp-server-bedrock-image

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page