> ## Documentation Index
> Fetch the complete documentation index at: https://mcp-server-langgraph.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 15. Memory Checkpointing for Stateful Agents

> Architecture Decision Record: 15. Memory Checkpointing for Stateful Agents

# 15. Memory Checkpointing for Stateful Agents

Date: 2025-10-13

## Status

Accepted

## Category

Data & Storage

## Context

Conversational agents need:

* Multi-turn conversations
* Context retention
* State persistence across restarts

Stateless agents lose context every request, degrading UX.

## Decision

Use **LangGraph MemorySaver** for conversation state checkpointing.

```python theme={null}
from langgraph.checkpoint.memory import MemorySaver

memory = MemorySaver()
graph = graph_builder.compile(checkpointer=memory)
```

## Consequences

### Positive

* **Multi-Turn Conversations**: Context preserved
* **User Experience**: Natural conversation flow
* **State Recovery**: Resume after crashes

### Negative

* **Memory Usage**: State grows with conversations
* **Persistence**: MemorySaver not persistent (future: Redis)

## Future Enhancements

* Redis checkpointer for distributed deployments
* State compression for long conversations

## References

* Implementation: `src/mcp_server_langgraph/core/agent.py:206-214`