Prompt
What framework should I use for agents with memory and tools?
Latest observation
Oct 9, 2026
OpenAI APIWeb search: off
If you want to build agents with memory and tools, the best framework depends on how much control you want versus how much built-in orchestration you need.
Good options
1. LangGraph
- Best for: robust agent workflows, memory, tool use, multi-step reasoning
- Why: It gives you a graph/state-machine approach, which is much better than a simple “loop agent” for reliable behavior
- Use it if: you want production-grade agents with explicit control over state, retries, branching, and long-running memory
2. LangChain
- Best for: quick prototyping and lots of integrations
- Why: Huge ecosystem of tools, retrievers, memory abstractions, and agent patterns
- Use it if: you want to get something working fast, and don’t mind some complexity or abstraction overhead
3. LlamaIndex
- Best for: RAG-heavy agents and knowledge access
- Why: Very strong for retrieval, indexing, and connecting agents to external knowledge sources
- Use it if: memory is mostly about document/knowledge retrieval, not just conversation state
4. Microsoft AutoGen
- Best for: multi-agent collaboration
- Why: Good if you want multiple specialized agents talking to each other
- Use it if: your use case is orchestration between agents, not just one agent with tools
My recommendation
- Single agent with tools + memory: LangGraph
- Knowledge-intensive agent: LangGraph + LlamaIndex
- Multi-agent system: AutoGen or LangGraph
- Fastest path to a demo: LangChain
Practical note on “memory”
There are usually two kinds:
- Short-term memory: conversation state, scratchpad, working context
- Long-term memory: saved facts, user preferences, documents, embeddings
Framework choice matters, but a lot of “memory” is really something you design yourself:
- store state in a DB
- save summaries
- use vector search for retrieval
- keep explicit agent state
Bottom line
If you’re starting today and want something reliable and scalable, I’d choose:
LangGraph + a vector store + optional LlamaIndex for retrieval
If you want, I can also give you a decision table based on your use case, or recommend a stack for Python vs TypeScript.