Amazon Nova Canvas
STDIOMCP server for generating images using Amazon Nova Canvas.
MCP server for generating images using Amazon Nova Canvas.
MCP server for generating images using Amazon Nova Canvas
generate_image
generate_image_with_colors
uv
from Astral or the GitHub READMEuv python install 3.10
aws configure
or environment variablesConfigure the MCP server in your MCP client configuration (e.g., for Amazon Q Developer CLI, edit ~/.aws/amazonq/mcp.json
):
{ "mcpServers": { "awslabs.nova-canvas-mcp-server": { "command": "uvx", "args": ["awslabs.nova-canvas-mcp-server@latest"], "env": { "AWS_PROFILE": "your-aws-profile", "AWS_REGION": "us-east-1", "FASTMCP_LOG_LEVEL": "ERROR" }, "disabled": false, "autoApprove": [] } } }
or docker after a successful docker build -t awslabs/nova-canvas-mcp-server .
:
# fictitious `.env` file with AWS temporary credentials AWS_ACCESS_KEY_ID=ASIAIOSFODNN7EXAMPLE AWS_SECRET_ACCESS_KEY=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY AWS_SESSION_TOKEN=AQoEXAMPLEH4aoAH0gNCAPy...truncated...zrkuWJOgQs8IZZaIv2BXIa2R4Olgk
{ "mcpServers": { "awslabs.nova-canvas-mcp-server": { "command": "docker", "args": [ "run", "--rm", "--interactive", "--env", "AWS_REGION=us-east-1", "--env", "FASTMCP_LOG_LEVEL=ERROR", "--env-file", "/full/path/to/file/above/.env", "awslabs/nova-canvas-mcp-server:latest" ], "env": {}, "disabled": false, "autoApprove": [] } } }
NOTE: Your credentials will need to be kept refreshed from your host
To install Amazon Nova Canvas MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @awslabs/nova-canvas-mcp-server --client claude
The MCP server uses the AWS profile specified in the AWS_PROFILE
environment variable. If not provided, it defaults to the "default" profile in your AWS configuration file.
"env": { "AWS_PROFILE": "your-aws-profile", "AWS_REGION": "us-east-1" }
Make sure the AWS profile has permissions to access Amazon Bedrock and Amazon Nova Canvas. The MCP server creates a boto3 session using the specified profile to authenticate with AWS services. Your AWS IAM credentials remain on your local machine and are strictly used for using the Amazon Bedrock model APIs.