Claude Prompts MCP Server

# Chains: Lifecycle & Concepts > Status: canonical Chains break complex workflows into discrete, manageable reasoning steps. ## Why This Matters | Problem | Solution | Result | |---------|----------|--------| | **Cognitive Overload** | Discrete Steps | Higher accuracy on complex tasks | | **Lost Context** | State Management | Data flows cleanly from A to B | | **Black Box** | Visible Progress | User sees/verifies intermediate steps | --- ## The Lifecycle Chains are not just a list of prompts. They are a managed **state machine**. ### 1. Init User invokes a chain (`>>research_chain`). The server creates a **Session** ID (`chain-research#123`). ### 2. Plan The server maps dependencies. - Step A: No dependencies. - Step B: Needs A. - Step C: Needs B. ### 3. Emit & Execute The server tells the client: "Run Step A". Client runs prompt → returns output. ### 4. Persist Server saves output to `runtime-state/chain-sessions.json`. Server checks dependencies: "Step B is now unblocked." ### 5. Loop Repeat until all steps complete. --- ## Session Management Chains persist across messages. You don't need to feed the entire history back to the model. - **Storage**: `server/runtime-state/chain-sessions.json` - **Resume**: Just provide `chain_id` + `user_response`. - **Debug**: Inspect the JSON file to see variable state at any point. ### Automatic Resume The MCP server recognizes active sessions. If you reply to a chain step, it automatically routes your response to the running session, restoring the execution context.