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mcp-server-amazon-bedrock

MCP.Pizza Chef: zxkane

The mcp-server-amazon-bedrock is a Model Context Protocol (MCP) server that connects to Amazon Bedrock's Nova Canvas model to enable AI-driven image generation from textual descriptions. It supports advanced features such as negative prompts for refining image outputs, configurable image dimensions and quality, and deterministic generation through seed control. Designed for developers with an AWS account and proper credentials, this server offers robust input validation and error handling to ensure reliable and flexible image creation workflows within MCP-enabled environments.

Use This MCP server To

Generate AI images from text prompts in real-time Refine image outputs using negative prompt controls Configure image size and quality dynamically Produce deterministic images with seed-based generation Integrate Amazon Bedrock image generation into MCP workflows

README

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Amazon Bedrock MCP Server

A Model Control Protocol (MCP) server that integrates with Amazon Bedrock's Nova Canvas model for AI image generation.

Amazon Bedrock Server MCP server

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.

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.

mcp-server-amazon-bedrock FAQ

What AWS prerequisites are needed to use this MCP server?
You need an active AWS account with Amazon Bedrock and Nova Canvas model access, plus properly configured AWS credentials with required permissions.
How does the server handle image generation quality and size?
It offers flexible configuration options allowing you to set image dimensions and quality parameters to suit your needs.
Can I control the randomness of generated images?
Yes, the server supports deterministic image generation through seed control to reproduce consistent outputs.
What is the role of negative prompts in this server?
Negative prompts help refine and control the composition of generated images by specifying undesired elements.
What Node.js version is required to run this MCP server?
Node.js version 18 or higher is required for proper operation.
How does the server ensure input reliability?
It includes robust input validation and error handling to maintain stable and predictable image generation.
Is this MCP server limited to Amazon Bedrock only?
Yes, this server specifically integrates with Amazon Bedrock's Nova Canvas model for image generation.
Can this MCP server be used with other LLM providers?
While it focuses on Amazon Bedrock for image generation, it can be part of MCP workflows that also use models from OpenAI, Anthropic Claude, or Google Gemini.