docs: add Vibecoding guide with Mem0 integration (#4511)
This commit is contained in:
Kartik
@@ -40,6 +40,7 @@
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"icon": "rocket",
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"pages": [
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"platform/overview",
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"vibecoding",
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"platform/mem0-mcp",
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"platform/platform-vs-oss",
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"platform/quickstart"
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@@ -142,6 +143,7 @@
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"icon": "rocket",
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"pages": [
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"open-source/overview",
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"vibecoding",
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"open-source/python-quickstart",
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"open-source/node-quickstart"
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]
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@@ -302,6 +304,7 @@
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"icon": "square-terminal",
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"pages": [
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"openmemory/overview",
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"vibecoding",
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"openmemory/quickstart",
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"openmemory/integrations"
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]
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@@ -0,0 +1,181 @@
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---
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title: "Vibecoding with Mem0"
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sidebarTitle: "Vibecoding"
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description: "Agent skills, starter prompts, and setup for building with Mem0 using AI coding tools."
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icon: "wand-magic-sparkles"
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---
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These docs are designed to be easily consumable by LLMs. Each page has a button that lets you copy the page as Markdown or paste directly into ChatGPT, Claude, or any AI coding tool.
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We follow the llms.txt standard:
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- [llms.txt](https://docs.mem0.ai/llms.txt)
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<CardGroup cols={2}>
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<Card title="Get an API Key" icon="key" href="https://app.mem0.ai">
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Sign up for Mem0 Platform and start building
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</Card>
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<Card title="Quickstart" icon="rocket" href="/platform/quickstart">
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Store your first memory in under 5 minutes
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</Card>
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</CardGroup>
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## Agent Skills
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Teach your coding assistant how to build with Mem0:
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```bash
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npx skills add https://github.com/mem0ai/mem0 --skill mem0
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```
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Works with Claude Code, Cursor, Windsurf, and any assistant that supports skills. Once installed, your assistant understands Mem0's full API, framework integrations, and common patterns.
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## Claude Code Plugin
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The [OpenMemory plugin](https://github.com/mem0ai/claude-code-plugin) gives Claude Code **persistent memory across sessions, projects, and teams** — automatically.
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<Steps>
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<Step title="Get your API key">
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Sign up at [app.openmemory.dev](https://app.openmemory.dev).
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</Step>
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<Step title="Install the plugin">
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```bash
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/plugin add mem0ai/claude-code-plugin
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```
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</Step>
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<Step title="Set your environment variable">
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```bash
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export OPENMEMORY_API_KEY="your-key-here"
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```
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</Step>
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<Step title="Start coding">
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The plugin activates automatically. It captures decisions at session end, preserves context during compaction, and retrieves relevant memories at session start.
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</Step>
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</Steps>
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## MCP Server Setup
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Connect Cursor, Windsurf, Claude Desktop, or any MCP-compatible client to Mem0.
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<Tabs>
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<Tab title="OpenMemory Hosted">
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Sign up at [app.openmemory.dev](https://app.openmemory.dev), then pick your client:
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<CodeGroup>
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```bash Claude Desktop
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npx @openmemory/install --client claude --env OPENMEMORY_API_KEY=your-key
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```
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```bash Cursor
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npx @openmemory/install --client cursor --env OPENMEMORY_API_KEY=your-key
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```
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```bash Windsurf
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npx @openmemory/install --client windsurf --env OPENMEMORY_API_KEY=your-key
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```
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</CodeGroup>
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For full setup options, see [OpenMemory Quickstart](/openmemory/quickstart).
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</Tab>
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<Tab title="Mem0 Platform MCP">
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Get your API key from [app.mem0.ai](https://app.mem0.ai), then add to your MCP config:
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```json
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{
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"mcpServers": {
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"mem0": {
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"command": "uvx",
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"args": ["mem0-mcp-server"],
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"env": {
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"MEM0_API_KEY": "m0-...",
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"MEM0_DEFAULT_USER_ID": "your-handle"
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}
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}
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}
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}
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```
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For Docker, Smithery, and advanced options, see [Mem0 MCP Setup](/platform/mem0-mcp).
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</Tab>
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</Tabs>
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## Universal Starter Prompt
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Copy this into any AI tool to start building with Mem0:
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```text
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I want to start building with Mem0 — a self-improving memory layer for LLM
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applications that gives agents persistent context across sessions.
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## Mem0 Resources
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**Documentation:**
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- Main docs: https://docs.mem0.ai
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- Platform Quickstart: https://docs.mem0.ai/platform/quickstart
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- OSS Python Quickstart: https://docs.mem0.ai/open-source/python-quickstart
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- OSS Node.js Quickstart: https://docs.mem0.ai/open-source/node-quickstart
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- API Reference: https://docs.mem0.ai/api-reference
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- Full LLM-friendly docs: https://docs.mem0.ai/llms.txt
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**Code & Examples:**
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- Core repo: https://github.com/mem0ai/mem0
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- Python SDK: pip install mem0ai
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- TypeScript SDK: npm install mem0ai
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- Cookbooks: https://docs.mem0.ai/cookbooks/overview
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**What Mem0 Does:**
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Mem0 is a memory layer for AI apps — managed (Mem0 Platform) or self-hosted
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(Open Source). It stores, retrieves, and manages user memories so agents
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remember preferences, learn from interactions, and personalize over time.
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Sub-50ms retrieval. Dual storage: vector embeddings + graph databases.
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**Architecture Overview:**
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- Memory is scoped by user_id, agent_id, or run_id
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- Core operations: add, search, update, delete
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- Memory types: factual (preferences, facts), episodic (past interactions),
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semantic (concept relationships), working (session state)
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- Integration pattern: retrieve relevant memories → generate response → store
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new memories
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**Quick Usage (Python Platform):**
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from mem0 import MemoryClient
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client = MemoryClient(api_key="m0-xxx")
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client.add("I prefer dark mode and use VS Code.", user_id="user1")
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results = client.search("What editor do they use?", user_id="user1")
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**Quick Usage (JavaScript Platform):**
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import MemoryClient from 'mem0ai';
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const client = new MemoryClient({ apiKey: 'm0-xxx' });
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await client.add([{ role: "user", content: "I prefer dark mode." }], { user_id: "user1" });
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const results = await client.search("What editor?", { user_id: "user1" });
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**Quick Usage (Python Open Source):**
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from mem0 import Memory
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m = Memory()
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m.add("I prefer dark mode and use VS Code.", user_id="user1")
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results = m.search("What editor do they use?", user_id="user1")
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Help me integrate Mem0 into my project. Start by asking what I'm building,
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what language/framework I'm using, and whether I want managed or self-hosted.
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```
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## Go Deeper
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<CardGroup cols={2}>
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<Card title="Platform Quickstart" icon="cloud" href="/platform/quickstart">
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Get started with the managed API
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</Card>
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<Card title="Open Source" icon="code-branch" href="/open-source/overview">
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Self-host with full control
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</Card>
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<Card title="Cookbooks" icon="book" href="/cookbooks/overview">
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Production-ready tutorials and examples
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</Card>
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<Card title="API Reference" icon="code" href="/api-reference">
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Explore every REST endpoint
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</Card>
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</CardGroup>
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