This MCP server implementation for Spinnaker, developed by Dion Hagan, enables AI models to interact with Spinnaker deployments, pipelines, and applications through a standardized interface. It provides tools for retrieving application and pipeline data, as well as triggering pipeline executions. The server maintains context about Spinnaker deployments and refreshes it periodically. Built with TypeScript and leveraging Express.js, it offers a RESTful API and WebSocket support for real-time updates. This implementation is particularly useful for DevOps teams and SREs looking to incorporate AI-driven decision making into their CI/CD processes, enabling use cases like automated deployment management, intelligent pipeline orchestration, and AI-assisted incident response.
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Retrieves a list of monitored Spinnaker applications and their current state.
Retrieves all pipelines for a specific application. Parameters: application (string)
Triggers a pipeline execution for a specific application. Parameters: application (string), pipelineId (string), parameters (object: version (string), environment (string))
