The Gist: Chaplin enables Operations teams to autonomously analyze AWS Health Events through AI agents without waiting for TAM support, by exposing AWS Health APIs via the Model Context Protocol as tools for Claude and other MCP clients.
AWS demonstrates an open-source tool called Chaplin that leverages AI agents via the Model Context Protocol (MCP) to independently analyze AWS Health Events. This allows Operations teams to ask questions in natural language and receive contextually relevant answers directly from Claude or similar assistants regarding planned maintenance, deprecations, and lifecycle events.
The problem is structural: Enterprises with dozens to hundreds of AWS accounts receive a flood of Health Events daily – service changes, maintenance windows, security patches, deprecations like Amazon Linux 2 end-of-life or RDS version transitions. These events are distributed across accounts and regions. Operations teams today have two options: they build static BI dashboards with predefined schemas, or they wait for Technical Account Managers (TAMs) to interpret events, leading to delays in critical decisions. The result is time spent on reactive firefighting rather than strategic planning.
Chaplin (Customer Health and Planned Lifecycle Intelligence Nexus) addresses this through agentic AI. The tool exposes AWS Health APIs and metadata as tools via the Model Context Protocol – a standard that structurally connects AI assistants with external systems. Operators can ask natural language questions directly from Claude, Kiro CLI, or other MCP-compatible clients: “Show RDS lifecycle events for the next 60 days,” “Summarize EC2 events by urgency,” “Which security patches affect Production?,” “Which maintenance windows impact high-priority apps?” The agent searches, filters, and contextualizes the data without requiring a predefined dashboard.
For CTOs, the technical leverage is significant: MCP allows combining AWS Health data with other enterprise-relevant contexts – such as resource tags, environment labels, ownership information – and orchestrating this with other MCP tools like Jira, GitHub, or ServiceNow in the same workflow. AWS also plans to directly link upcoming Health Events with AWS Transform Templates, which Chaplin can automatically surface. This relieves TAM burden and makes teams self-sufficient in prioritization and planning.
The code is available as open source in the AWS Health Agentic Assistant repository on GitHub. The deployment architecture is based on Amazon Bedrock (as LLM backend) and uses standardized MCP integration, enabling portability beyond Claude.
Source: aws.amazon.com · Published June 25, 2026
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