io.github.askadvaith/mcp-state-sidecar

Design a state persistence plan for my multi-agent research workflow. I need to store task progress, agent context, and retry logs, and resume from the last checkpoint after a restart. Provide a state schema and recovery flow.

A state model, checkpoint strategy, and recovery steps for interruption recovery.

I have an AI workflow with planner, executor, and reviewer agents. Design how to persist each agent’s inputs and outputs, current status, shared memory, and task dependencies for later tracing and auditing.

Clear state field definitions and storage recommendations for multi-agent traceability.

Explain how to add a durable state layer to a production multi-agent AI system, including retry handling, state consistency, concurrent update control, and deployment considerations.

A production-oriented fault-tolerance integration plan with operational best practices.