Commita488e1904deleted mem0/graphs/ and mem0-ts/src/oss/src/graphs/ when the v3 pipeline landed, and3f717e545reframed the docs as Platform-only, but the agent-facing context files were never updated. Agents reading them still believe OSS graph memory exists and propose graph_store config that cannot work. - AGENTS.md: drop graphs/ from the directory map and dependency tree, correct the provider table (4 categories, not 5; LLMs 24->18, vector stores 30->25, embeddings 15->12), and rewrite the Graph Memory section as Platform-only - skills: replace the OSS graph-memory prompt example and stop indexing /open-source/features/graph-memory, which 404s; also fix four other SECTION_MAP paths that no longer resolve - mem0/exceptions.py: DependencyError example referenced kuzu/graph_store - tests/test_telemetry.py: drop four mock_memory.config.graph_store lines; graph_store is not a MemoryConfig field and telemetry never reads it - CONTRIBUTING.md: add the three missing release tag prefixes (opencode-v*, pi-agent-v*, n8n-nodes-mem0-v*) and note Zapier deploys off-registry
Mem0 Skill for Claude
Add persistent memory to any AI application in minutes using Mem0 Platform.
What This Skill Does
When installed, Claude can:
- Set up Mem0 in your Python or TypeScript project
- Integrate memory into your existing AI app (LangChain, CrewAI, Vercel AI, OpenAI Agents, LangGraph, LlamaIndex, etc.)
- Generate working code using real API references and tested patterns
- Search live docs on demand for the latest Mem0 documentation
Installation
This skill is included automatically when you install the Mem0 plugin:
/plugin marketplace add mem0ai/mem0
/plugin install mem0@mem0-plugins
See the plugin README for full setup instructions.
Prerequisites
-
A Mem0 Platform API key (Get one here)
-
Python 3.10+ or Node.js 18+
-
Set the environment variable:
export MEM0_API_KEY="m0-your-api-key"
Quick Start
After installing, just ask Claude:
- "Set up mem0 in my project"
- "Add memory to my chatbot"
- "Help me search user memories with filters"
- "Integrate mem0 with my LangChain app"
- "Migrate my app from mem0 v2 to v3"
What's Inside
skills/mem0/
├── SKILL.md # Skill definition and instructions
├── README.md # This file
├── LICENSE # Apache-2.0
├── scripts/
│ └── mem0_doc_search.py # Search live Mem0 docs on demand
└── references/ # Documentation (loaded on demand)
├── quickstart.md # Full quickstart (Python, TS, cURL)
├── sdk-guide.md # All SDK methods (Python + TypeScript)
├── api-reference.md # REST endpoints, filters, memory object
├── architecture.md # Processing pipeline, lifecycle, scoping, performance
├── features.md # Retrieval, entity linking, categories, MCP, webhooks, multimodal
├── integration-patterns.md # LangChain, CrewAI, Vercel AI, LangGraph, LlamaIndex, etc.
└── use-cases.md # 7 real-world patterns with Python + TypeScript code
Links
License
Apache-2.0