Listing Container-based AI agent products

Start the listing wizard

1. Log into the AWS Marketplace Management Portal with your AWS seller account.

2. Select Products and then select Server in the navigation bar.

3. Select the Create server product dropdown menu and select Container option.

4. Select Generate product ID and product code.

5. Select Continue.

Step 1: Provide product Information

1. In Product information, enter:

   • Product title

   • Product logo S3 URL

   • Short description

   • Long description

   • Highlight (1-3)

2. Enter support details and add optional learning resources by choosing Add resource.

3. In the Product categories menu, choose 1-3 categories. We recommend that you choose at least one category from the AI Agents & Tools business categories.

4. Enter keywords to improve search discoverability.

5. (Optional) Add video and image assets according to the guidelines.

6. Choose Next.

Step 2: Configure AI Agent Container pricing

1. Choose pricing model.

   AgentCore pricing limitations

   If the container image is utilizing AgentCore, you're limited to Monthly, BYOL, or Free pricing models.

2. Select Next.

3. In Set prices.

4. Select Next.

Step 3: Specify refund policy

1. Enter a refund policy.

2. Select Next.

Note

If you chose the free product pricing model, you do not have to enter a refund policy.

Step 4: Configure EULA

1. Choose Standard Contract for AWS Marketplace or Custom EULA.

   Note

   If you choose Custom EULA, enter a URL for the end-user license agreement.

2. Select Next.

Step 5: Add repositories

1. Add an initial repository for your container product.

   Note

   Repository names must be unique across all products in your seller account. You can create up to 50 repositories per product.

2. Select Next.

Step 6: Configure offer availability / Allow list

1. In Configure offer availability, choose your geographic availability settings.

2. Select Next.

3. In Configure allowlist, list any AWS accounts that should have access to the listing while in the limited state.

4. Select Submit to create a new change request for limited visibility testing.

   Wait 10-15 minutes until your request status is in the Succeeded state.

Step 7: Upload Container images and artifacts to repository

Note

See AWS Bedrock AgentCore Runtime for AWS Marketplace on how to integrate AgentCore with your Container Image.

1. Locate the URL for the ECR repository:

   • Open the Server products page in AWS Marketplace Management Portal.

   • Select your container product to view the details.

   • Select the Repositories tab to copy the URL of the repository.

2. Select View push commands to open a list of instructions, including commands you can use to push Docker container images and Helm charts to that repository. For general information about how to push container images and other artifacts to repositories, see Pushing an image in the Amazon Elastic Container Registry User Guide.

   Note

   You can use the following Amazon Elastic Container Registry (Amazon ECR) API operations when calling docker pull or docker push:

   • DescribeImages - Use this to review the metadata about the images in a repository.

   • GetAuthorizationToken - Use to authenticate before uploading artifacts to the repository, then use docker pull or docker push commands.

   • ListImages - Use to view a list of images you pushed.

3. Use the commands listed to push any needed artifacts from your local repository to the AWS Marketplace repository for your product.

   Note

   The tag that you provide in the push commands is used to differentiate the version of the artifact that you are uploading to the repository. Use a tag that makes sense for the version the artifacts are a part of.

4. Repeat for each container image or artifact you need in your version.

   Note

   Your version can include up to 50 container images or artifacts in each delivery option. Refer to the following procedure for more information about delivery options.

5. After you upload your artifacts, you're ready to create the version of your product.

   Note

   Your container images are scanned automatically to see if they meet the Container-based product requirements for AWS Marketplace. For more information, see Container product scans for security issues.

Step 8: Add New Product Version with Assets

1. Open the Server products page in the AWS Marketplace Management Portal.

2. Select your container product and click the Request changes dropdown menu, select Update versions, and select Add new version.

3. In Delivery options, enter:

   • Version title

   • Release notes

4. Select Add delivery option.

5. For Delivery method, select Container image and fill in:

   • Supported services: select the environment that buyers can launch the software in.

     Note

     Amazon Bedrock AgentCore is currently available only for preview. See AWS Bedrock AgentCore Runtime for AWS Marketplace for more details.

   • Container image: Repository URL and version tag you specified previously.

   • Delivery option title and Deployment option description: Enter a title and description for this delivery option.

   • Usage instructions: Enter detailed information to help your buyers use your software after launching it.

     Important

     For Bedrock AgentCore service, Type requires a selection of either: AI Agent or MCP Server

6. Select Add version.

   Wait and refresh the page until the request status shows Succeeded.

   Adding a new version automatically scans the container images for vulnerabilities.

Step 9: Review Product Listing and Publish to Public

1. Open the Server products page in the AWS Marketplace Management Portal.

2. Select your container product in the list.

3. Select View on AWS Marketplace.

4. Review your product detail page for accuracy. Ensure the usage instructions sufficiently guide the buyer through the necessary steps to launch your product.

5. Submit an Update visibility request to public:

   • From the Server products page, on the Current server product tab, select the container-based product that you want to modify. From the Request changes dropdown, choose Update visibility.

Container deployment details

Container deployment packages your AI agent or tool as a containerized application that customers can run in their own AWS environments. This approach provides the following benefits:

• Data remains within the customer's environment

• Customizable deployment configurations

• Supported integration with Bedrock AgentCore Runtime and customer's existing infrastructure

When listing a containerized agent, provide clear deployment instructions, resource requirements, and configuration options to ensure successful customer implementation.

Important

Amazon Bedrock AgentCore is currently in preview.

Technical requirements for Bedrock AgentCore Runtime Containers

Note

See AWS Bedrock AgentCore Runtime for AWS Marketplace for more details.

When creating container-based AI agent products for AWS Marketplace, follow these requirements:

MCP Server Requirements

• Transport: Stateless streamable-http only

• Session Management: Platform automatically adds Mcp-Session-Id header for session isolation

• Host: Container must listen on 0.0.0.0

• Port: Container must expose port 8000 for MCP server communication

• Path: /mcp - POST endpoint for receiving MCP RPC messages. InvokeAgentRuntime for MCP servers will pass through requests to this path.

• Protocol: The MCP server must support the MCP protocol including protocol messages 'tools/list' and 'tools/call' (supported by common framework such as FastMCP).

Agent Requirements

• /ping Endpoint: GET endpoint for health checks

• /invocations Endpoint: POST endpoint for agent interactions

• Docker Container: ARM64 containerized deployment package

• Port: Container must expose port 8080 for HTTP-based agent communication

• No hardcoded credentials

• Free of Common Vulnerabilities and Exposures (CVEs)

Usage instructions

Ensure instructions thoroughly guides customers through launching and configuring the product. Refer to Creating AMI and container product usage instructions for AWS Marketplace.

Testing and validation

Prior to publishing your MCP-compatible agent or tool to public, thoroughly test your implementation:

• Verify usage instructions provides necessary information to launch and configure the product.

• Test authentication flows and error handling

• Validate performance under various load conditions

• Ensure compatibility with popular MCP clients

• Document any client-specific configuration requirements

Best Practices and Recommendations

Documentation Requirements

When listing an Model Context Protocol-compatible agent or tool on AWS Marketplace, include comprehensive documentation:

• Detailed capability descriptions and examples

• Authentication and configuration instructions

• Sample code for common integration scenarios

• Troubleshooting guides and error reference

• Performance considerations and best practices

Additional resources

For more information about implementing Model Context Protocol in your AI agent or tool, refer to these resources:

• Amazon Bedrock AgentCore Documentation

• AWS Bedrock AgentCore Runtime for AWS Marketplace

• Container Technical Requirements