v0.1.6·Building Workflows
State Management
Manage agent and workflow state effectively
State Management
Effective state management is crucial for building reliable multi-turn agent workflows.
Types of State
Conversation State
Track messages and interaction history:
Agent State
Store agent-specific information:
User Context
Maintain user-specific information:
Application State
Track workflow-level state:
State Storage Strategies
In-Memory State
Best for single-session interactions:
- Fast access
- No persistence
- Lost on page refresh
- Suitable for temporary data
Session Storage
Persist data for current browser session:
Local Storage
Persist data across sessions:
Backend Storage
Durable persistence:
- Database storage
- API synchronization
- Cross-device access
- Audit trails
State Updates
Immutable Updates
Always create new state objects:
Batching Updates
Group related changes:
Async State Management
Handle async operations:
Cleanup and Memory Management
Session Cleanup
Clear state on logout or session end:
Memory Optimization
Limit state size:
- Archive old messages
- Remove completed tasks
- Clear temporary data
- Implement data expiration
Debugging State
State Snapshots
Capture state at key points:
State Validation
Verify state consistency:
Next Steps
Learn about data management in MCPs Overview and explore practical examples in Examples & Use Cases.
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