The Amazon Bedrock AgentCore Runtime service contract outlines the communication protocols necessary for integrating custom agent applications with AWS's managed hosting environment. Currently in preview, this contract supports two primary protocols: HTTP and MCP (Model Context Protocol).
For the HTTP protocol, agents must be deployed as containerized applications on an ARM64 platform, listening on port 8080. The main interaction endpoint is `/invocations`, which processes incoming requests with JSON input and provides JSON or Server-Sent Events (SSE) output. This endpoint facilitates various use cases, including direct user interactions, API integrations, and real-time streaming responses. Agents can respond in two formats: JSON for quick, deterministic responses and SSE for incremental updates during long-running operations.
The `/ping` endpoint is also crucial, allowing users to verify the agent's operational status. It returns a status code indicating health, with options for "Healthy" or "HealthyBusy" to denote the system's readiness to accept new tasks.
The MCP protocol requires agents to implement specific transport and session management features, operating on port 8000. The `/mcp` endpoint processes RPC messages and supports JSON-RPC formatted responses. This protocol is designed for tool invocation, agent capability discovery, and managing multi-step workflows.
Overall, the AgentCore Runtime service contract provides a structured framework for developers to create and manage agents within the Amazon Bedrock ecosystem, ensuring efficient communication and operational integrity. As the service is still in preview, users should be aware that specifications may evolve.
The search results for "agentcore" on Qiita reveal a variety of articles and discussions centered around Amazon Bedrock AgentCore, a service designed for deploying AI agents and managing their runtime environments. The content includes insights from multiple authors who explore different aspects of AgentCore, including its integration with AWS services like CodePipeline and Terraform for secure updates, as well as practical applications such as creating AI chat applications using Next.js and AWS Amplify.
Key articles highlight the deployment of MCP servers and the use of Strands Agents and S3 Vectors in building Retrieval-Augmented Generation (RAG) systems. The discussions also touch on the technical challenges and solutions encountered while working with AgentCore, such as issues with the agentcore configure command and setting environment variables for the runtime.
Several authors provide tutorials and hands-on experiences, emphasizing the ease of use and security features of AgentCore, which allows developers to create secure, production-ready AI agents without extensive setup time. The articles reflect a growing interest in AI technologies and the practical implications of using Amazon Bedrock AgentCore for various applications.
Overall, the search results illustrate a vibrant community of developers sharing knowledge and experiences related to AgentCore, showcasing its potential in the AI landscape and encouraging further exploration and experimentation with the platform.
AWS Bedrock AgentCore Runtime Service Contract documentation explaining the interaction between agents and runtime services, detailing service contract specifications, communication protocols, and operational guidelines for agent runtime environments. This technical guide provides insights into how runtime services manage and facilitate agent operations, ensuring robust and standardized communication mechanisms within the AgentCore ecosystem.