AWS bedrock-agentcore documentation change
Summary
Updated documentation to reflect a change from using a Python-based 'starter toolkit' to a Node.js-based 'AgentCore CLI' for deployment. Changed commands from 'agentcore configure' and 'agentcore launch' to 'agentcore create' and 'agentcore deploy', and updated the deployment artifact process from Docker/ECR to packaging/S3.
Security assessment
The changes are procedural updates for tooling and deployment workflow. While the documentation continues to mention the requirement for a Cognito user pool and OAuth tokens for secure access, this is not a new addition. There is no evidence in the diff that these changes were made to address a specific security vulnerability, weakness, or incident. The updates appear to be routine documentation maintenance for a changed CLI interface and deployment process.
Diff
diff --git a/bedrock-agentcore/latest/devguide/runtime-mcp.md b/bedrock-agentcore/latest/devguide/runtime-mcp.md index e4d411e98..71000ebcc 100644 --- a//bedrock-agentcore/latest/devguide/runtime-mcp.md +++ b//bedrock-agentcore/latest/devguide/runtime-mcp.md @@ -171 +171 @@ You can also test your server using the MCP Inspector as described in Local test -Install the AgentCore starter toolkit: +Install the AgentCore CLI: @@ -174 +174 @@ Install the AgentCore starter toolkit: - pip install bedrock-agentcore-starter-toolkit + npm install -g @aws/agentcore @@ -176 +176 @@ Install the AgentCore starter toolkit: -You use the starter toolkit to deploy your agent to AgentCore Runtime. +You use the AgentCore CLI to deploy your agent to AgentCore Runtime. @@ -195 +195 @@ Create a new file called `requirements.txt`, add the following to it: -### Configure your MCP server for deployment +### Create your project for deployment @@ -197 +197 @@ Create a new file called `requirements.txt`, add the following to it: -Before configuring your deployment, you need to set up a Cognito user pool for authentication as described in Set up Cognito user pool for authentication. This provides the OAuth tokens required for secure access to your deployed server. +Before creating your project, you need to set up a Cognito user pool for authentication as described in Set up Cognito user pool for authentication. This provides the OAuth tokens required for secure access to your deployed server. @@ -203,14 +203 @@ Starting **October 7, 2025** , Amazon Bedrock AgentCore uses a Service-Linked Ro -After setting up authentication, create the deployment configuration: - - - agentcore configure -e my_mcp_server.py --protocol MCP - -This will start a guided prompt workflow: - - * For execution role, you need to have an IAM execution role with appropriate permissions - - * For ECR, just press `enter` to skip and it will auto-create - - * For dependency file, the CLI will auto-detect from current directory - - * For OAuth, type `yes` and provide the discovery URL and client ID token +After setting up authentication, scaffold a new project with MCP protocol: @@ -218,0 +206 @@ This will start a guided prompt workflow: + agentcore create --protocol MCP @@ -219,0 +208 @@ This will start a guided prompt workflow: +Follow the interactive prompts to provide a project name. The CLI scaffolds the project structure including an `agentcore/agentcore.json` configuration file. Copy your `my_mcp_server.py` file into the generated project's agent code directory, and ensure the entrypoint in `agentcore/agentcore.json` points to your server file. @@ -226 +215 @@ Deploy your agent: - agentcore launch + agentcore deploy @@ -230 +219 @@ This command will: - 1. Build a Docker container with your agent + 1. Package your agent code and dependencies @@ -232 +221 @@ This command will: - 2. Push it to Amazon ECR + 2. Upload the deployment artifact to Amazon S3 @@ -334,12 +323 @@ For more information, see [Auth0 Dynamic Client Registration documentation](http -### Step 5: Configure your MCP server for deployment - -After setting up authentication, create the deployment configuration: - - - agentcore configure -e my_mcp_server.py --protocol MCP - -This will start a guided prompt workflow: - - * For execution role, you need to have an IAM execution role with appropriate permissions - - * For ECR, just press `enter` to skip and it will auto-create +### Step 5: Create your project for deployment @@ -347 +325 @@ This will start a guided prompt workflow: - * For OAuth, type `yes` and provide the discovery URL and audience. +After setting up authentication, scaffold a new project with MCP protocol: @@ -349,0 +328 @@ This will start a guided prompt workflow: + agentcore create --protocol MCP @@ -350,0 +330 @@ This will start a guided prompt workflow: +Follow the interactive prompts to provide a project name. The CLI scaffolds the project structure including an `agentcore/agentcore.json` configuration file. Copy your `my_mcp_server.py` file into the generated project's agent code directory, and ensure the entrypoint in `agentcore/agentcore.json` points to your server file. @@ -357 +337 @@ Deploy your agent: - agentcore launch + agentcore deploy @@ -361 +341 @@ This command will: - * Build a Docker container with your agent + * Package your agent code and dependencies @@ -363 +343 @@ This command will: - * Push it to Amazon ECR + * Upload the deployment artifact to Amazon S3 @@ -981 +961 @@ After running this script, note the following values for use in the deployment c - * Discovery URL: Used during the `agentcore configure` step + * Discovery URL: Used during the `agentcore create` step @@ -983 +963 @@ After running this script, note the following values for use in the deployment c - * Client ID: Used during the `agentcore configure` step + * Client ID: Used during the `agentcore create` step