Long-running agents fail when state lives only in a transcript or compaction summary. A context reset, a crash, or a model switch loses everything. This talk shows how to externalize agent state into a durable MCP capsule: goals in docs:// entries, progress in notes:// threads, artifacts as versioned blobs, definitions of done as guidance:// entries, and handoff notes that let a fresh worker session resume without re-exploring. We demonstrate the initializer-worker-reviewer pattern where a capsule serves as the rehydration layer between sessions, and show how signals coordinate actors without requiring persistent connections. The key insight: the capsule should answer a fresh worker's first questions — what is the goal, what changed, who is working, what should I verify, and what is the next safe step.