Amazon Bedrock MCP Server
About
This server integrates with Amazon Bedrock's Nova Canvas model to generate images from text descriptions using the Model Context Protocol. It is designed for developers and AI applications that need image generation with advanced control over composition, dimensions, and quality.
Details
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- MCP-Mirror
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- Generates high-quality images from text descriptions
- Supports negative prompts for refined composition
- Configurable image dimensions and quality levels
- Deterministic generation with seed control
- Robust input validation and error handling
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Amazon Bedrock MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install the npm package, configure AWS credentials via environment variables, the AWS credentials file, or an IAM role. Integrate with Claude Desktop by adding the server configuration to claude_desktop_config.json. Invoke the generate_image tool with a required prompt and optional parameters such as negativePrompt, width, height, quality, cfg_scale, seed, and numberOfImages.
generate_image
Generate image(s) using Amazon Nova Canvas model. The returned data is Base64-encoded string that represent each image that was generated.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"amazon bedrock mcp server": {
"amazon-bedrock": {
"command": "npx",
"args": [
"-y",
"@zxkane/mcp-server-amazon-bedrock"
],
"env": {
"AWS_PROFILE": "",
"AWS_ACCESS_KEY_ID": "",
"AWS_SECRET_ACCESS_KEY": "",
"AWS_REGION": ""
}
}
}
}
}McpServers
{
"amazon-bedrock": {
"command": "npx",
"args": [
"-y",
"@zxkane/mcp-server-amazon-bedrock"
],
"env": {
"AWS_PROFILE": "",
"AWS_ACCESS_KEY_ID": "",
"AWS_SECRET_ACCESS_KEY": "",
"AWS_REGION": ""
}
}
}Amazon Bedrock MCP Server
A Model Control Protocol (MCP) server that integrates with Amazon Bedrock's Nova Canvas model for AI image generation.
<a href="https://glama.ai/mcp/servers/9qw7dwpvj9"></a>
Features
- High-quality image generation from text descriptions using Amazon's Nova Canvas model
- Advanced control through negative prompts to refine image composition
- Flexible configuration options for image dimensions and quality
- Deterministic image generation with seed control
- Robust input validation and error handling
Prerequisites
1. Active AWS account with Amazon Bedrock and Nova Canvas model access
2. Properly configured AWS credentials with required permissions
3. Node.js version 18 or later
Installation
AWS Credentials Configuration
The server requires AWS credentials with appropriate Amazon Bedrock permissions. Configure these using one of the following methods:
1. Environment variables:
export AWS_ACCESS_KEY_ID=your_access_key
export AWS_SECRET_ACCESS_KEY=your_secret_key
export AWS_REGION=us-east-1 # or your preferred region
2. AWS credentials file (~/.aws/credentials):
[the_profile_name]
aws_access_key_id = your_access_key
aws_secret_access_key = your_secret_key
Environment variable for active profile:
export AWS_PROFILE=the_profile_name
3. IAM role (when deployed on AWS infrastructure)
Claude Desktop Integration
To integrate with Claude Desktop, add the following configuration to your settings file:
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"amazon-bedrock": {
"command": "npx",
"args": [
"-y",
"@zxkane/mcp-server-amazon-bedrock"
],
"env": {
"AWS_PROFILE": "your_profile_name", // Optional, only if you want to use a specific profile
"AWS_ACCESS_KEY_ID": "your_access_key", // Optional if using AWS credentials file or IAM role
"AWS_SECRET_ACCESS_KEY": "your_secret_key", // Optional if using AWS credentials file or IAM role
"AWS_REGION": "us-east-1" // Optional, defaults to 'us-east-1'
}
}
}
}
Available Tools
generate_image
Creates images from text descriptions using Amazon Bedrock's Nova Canvas model.
Parameters
- prompt (required): Descriptive text for the desired image (1-1024 characters)
- negativePrompt (optional): Elements to exclude from the image (1-1024 characters)
- width (optional): Image width in pixels (default: 1024)
- height (optional): Image height in pixels (default: 1024)
- quality (optional): Image quality level - "standard" or "premium" (default: "standard")
- cfg_scale (optional): Prompt adherence strength (1.1-10, default: 6.5)
- seed (optional): Generation seed for reproducibility (0-858993459, default: 12)
- numberOfImages (optional): Batch size for generation (1-5, default: 1)
Example Implementation
const result = await callTool('generate_image', {
prompt: "A serene mountain landscape at sunset",
negativePrompt: "people, buildings, vehicles",
quality: "premium",
cfg_scale: 8,
numberOfImages: 2
});
Prompt Guidelines
For optimal results, avoid negative phrasing ("no", "not", "without") in the main prompt. Instead, move these elements to the negativePrompt parameter. For example, rather than using "a landscape without buildings" in the prompt, use "buildings" in the negativePrompt.
For detailed usage guidelines, refer to the [Nova Canvas documentation][nova-canvas-doc].
Development
To set up and run the server in a local environment:
git clone https://github.com/zxkane/mcp-server-amazon-bedrock.git
cd mcp-server-amazon-bedrock
npm install
npm run build
Performance Considerations
Generation time is influenced by resolution (width and height), numberOfImages, and quality settings. When using higher values, be mindful of potential timeout implications in your implementation.
License
This project is licensed under the MIT License - see the LICENSE file for details.
[nova-canvas-doc]: https://docs.aws.amazon.com/nova/latest/userguide/image-gen-access.html
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