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langgraph-memory

Manage thread-scoped and cross-thread memory in LangGraph applications using checkpointers and stores.

Updated Feb 13, 2026
Search Tags:#state management#agent#memory#persistence#langgraph#chatbot
One-click install
npx skills add https://github.com/evanfang0054/x-codegen-agent --skill langgraph-memory
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langgraph-memory
Source: https://github.com/evanfang0054/x-codegen-agent/tree/main/.claude/skills/langgraph-memory
Command: npx skills add https://github.com/evanfang0054/x-codegen-agent --skill langgraph-memory

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of managing conversational history and persistent data within LangGraph applications, enabling agents to recall past interactions and user preferences.

Core Features & Use Cases

  • Short-Term Memory: Manages thread-scoped conversation history using checkpointers.
  • Long-Term Memory: Enables cross-thread data persistence via stores for user preferences and facts.
  • Use Case: Build a customer support chatbot that remembers a user's previous issues (long-term) and the current conversation flow (short-term) to provide more personalized and context-aware assistance.

Quick Start

Use the langgraph-memory skill to demonstrate saving and retrieving user preferences using a long-term memory store.

Frequently Asked Questions about langgraph-memory

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I manage short-term and long-term memory in LangGraph chatbots?▼

To manage LangGraph memory, use checkpointers for short-term thread-scoped conversation history and stores for long-term cross-thread data persistence, enabling agents to recall past interactions and user preferences.

What is the difference between thread-scoped and cross-thread memory in LangGraph state management?▼

Thread-scoped memory in LangGraph handles current conversation flow via checkpointers, while cross-thread memory persists user facts and preferences across sessions using stores for personalized agent assistance.

How do I persist user preferences across multiple chat sessions in a LangGraph agent?▼

Persist user preferences in LangGraph by utilizing long-term memory stores, such as InMemoryStore or PostgresStore, which allow cross-thread data access and manipulation through the configuration object.

Does LangGraph memory support Postgres as a storage backend for agent persistence?▼

Yes, LangGraph memory supports PostgresStore as a storage backend for agent persistence, alongside InMemoryStore, allowing nodes to access and manipulate both short-term and long-term memory effectively.

How do nodes access long-term memory stores through the LangGraph configuration object?▼

Nodes access long-term memory stores in LangGraph through the configuration object, enabling them to retrieve and manipulate cross-thread user preferences and facts during agent execution.

When should I use checkpointers versus stores for LangGraph state management?▼

Use checkpointers in LangGraph for short-term memory to manage thread-scoped conversation history, and use stores for long-term memory to persist cross-thread data like user preferences and past interaction facts.

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