Agent_Memory_Techniques: Master LLM Memory with 30 Ready‑to‑Run Notebooks
From the repo · “Agent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta, Zep, Graphiti, LoCoMo benchmarks, and production patterns.”
Use pre-built Jupyter notebooks to create conversational AI.
"A founder wants to create a conversational AI assistant that can help customers book travel itineraries. She uses the Agent Memory Techniques skill to set up a Jupyter notebook that incorporates a knowledge graph and episodic memory. After 1-2 hours of setup, she's able to ask Claude to retrieve customer travel history and suggest personalized booking options."
- •When you need to improve the conversational context and memory of your LLM-powered chatbot
- •When you want to experiment with different memory techniques such as conversation buffers, vector stores, and knowledge graphs
- •When you're working on a project that requires episodic and semantic memory, like dialogue systems or question-answering models
Run the `memgpt_example.ipynb` notebook to see a demonstration of how to use MemGPT for conversational memory
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/agent-memory-techniques && curl -fsSL https://workflowstacks.com/api/skills/agent-memory-techniques/claude-skill -o ~/.claude/skills/agent-memory-techniques/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/agent-memory-techniques && curl -fsSL https://workflowstacks.com/api/skills/agent-memory-techniques/claude-skill -o ~/.claude/skills/agent-memory-techniques/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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Do this with a working workflow
Pages we wrote and tested that put a skill like this to work — importable n8n templates, outcome guides and Claude Desktop configs.
Memory (knowledge graph) MCP config
Persistent memory across chats via a local knowledge graph.
Outcome guideRecover abandoned carts with personalized emails
Export abandoned carts to a Google Sheet and the workflow drafts a warm, specific win-back email for each — referencing the actual product, without desperate discount-spam. You review and send.
MCP configGitHub MCP config
Search repos, read code, open issues and PRs from Claude.
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