📖 The AI Tool Bible

AgentMemory vs LangGraph

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
AgentMemory
Agents
LangGraph
Agents
TaglineOpen-source persistent memory runtime for AI coding agents, with hybrid retrieval and zero external dependencies.Stateful, graph-based agent orchestration from LangChain.
CategoryAgentsAgents
PricingFree· Free, open-source (Apache 2.0); bring your own LLM API keyFreemium· Free open-source; LangGraph Platform paid
ModelMulti-model (Claude, Gemini, MiniMax, OpenRouter)BYO (Claude / GPT / open)
Editorial score—8.8 / 10
Use cases
agent-memorycoding-agentscontext-managementknowledge-graphmcp-server
stateful agentshuman-in-loopproduction
Pros
  • Zero external infrastructure: single Node process, JSON on disk
  • Triple-stream retrieval (BM25 + vectors + graph) with sub-20ms recall
  • Native plugins for Claude Code, Cursor, Cline, Windsurf, and 15+ agents
  • Apache 2.0, runs on your existing LLM subscription
  • Strong benchmark numbers (95.2% R@5 on LongMemEval-S)
  • Reliable, debuggable agent graphs
  • Built-in persistence + HITL
  • Production-grade
  • Tight LangSmith integration
Cons
  • Pre-1.0 (v0.9.27), expect breaking changes
  • Single-process JSON storage may not scale to team-wide deployments
  • Self-hosted only; you operate the runtime
  • Effectiveness depends on the LLM provider you wire in
  • Steeper learning curve than CrewAI
  • Verbose to set up
Websiteagent-memory.devwww.langchain.com
Pick AgentMemory if
  • ✅ Zero external infrastructure: single Node process, JSON on disk
  • ✅ Triple-stream retrieval (BM25 + vectors + graph) with sub-20ms recall
  • ✅ Native plugins for Claude Code, Cursor, Cline, Windsurf, and 15+ agents
  • ✅ Apache 2.0, runs on your existing LLM subscription
Pick LangGraph if
  • ✅ Reliable, debuggable agent graphs
  • ✅ Built-in persistence + HITL
  • ✅ Production-grade
  • ✅ Tight LangSmith integration
Compare a different pair →