add vibe coding instructions for setup

2 files changed, 387 insertions, 1 deletions

diff --git a/apps/docs/docs.json b/apps/docs/docs.json
index 82dfb629..9bd65c8c 100644
--- a/apps/docs/docs.json
+++ b/apps/docs/docs.json
@@ -71,7 +71,7 @@
 						"pages": [
 							{
 								"group": "Getting Started",
-								"pages": ["intro", "quickstart", "memory-vs-rag"]
+								"pages": ["intro", "vibe-coding", "quickstart", "memory-vs-rag"]
 							},
 							{
 								"group": "Memory API",
diff --git a/apps/docs/vibe-coding.mdx b/apps/docs/vibe-coding.mdx
new file mode 100644
index 00000000..54b00321
--- /dev/null
+++ b/apps/docs/vibe-coding.mdx
@@ -0,0 +1,386 @@
+---
+title: "Vibe Coding Setup"
+description: "Automatic Supermemory integration using AI coding agents"
+icon: "zap"
+sidebarTitle: "Automatic setup"
+---
+
+Get your AI coding agent to integrate Supermemory in minutes. Copy the prompt below, paste it into Claude/GPT/Cursor, and let it do the work.
+
+## Quick Setup
+
+<CardGroup cols={3}>
+	<Card title="MCP (Claude/Cursor)" icon="plug" href="#mcp-server">
+		Give your agent a way to reference and search through supermemory docs.
+  </Card>
+
+	<Card title="Copy Prompt" icon="copy" href="#the-prompt">
+    Paste one prompt, answer questions, get working code
+  </Card>
+
+  <Card title="Claude Code Skill" icon="terminal" href="#claude-code-skill">
+    Interactive guided setup
+  </Card>
+</CardGroup>
+
+## MCP Server
+
+Give your agent a way to reference and search through supermemory docs.
+
+### Quick Install
+
+```bash
+npx -y install-mcp@latest https://supermemory.ai/docs/mcp --client claude-code --oauth=no -y
+```
+
+Replace `claude` with: `cursor`, `opencode`, or `vscode`
+
+
+---
+
+## The Prompt
+
+<Note>
+**Copy everything in the code block below** and paste it into your AI coding agent. It will ask you questions and generate complete integration code.
+</Note>
+
+After adding the MCP, paste this in your agent session:
+
+<Accordion title="Copy prompt below." icon='copy'>
+```
+You are integrating Supermemory into my application. Supermemory provides user memory, semantic search, and automatic knowledge extraction for AI applications.
+
+Note: You can always reference the documentation by using the **SearchSupermemoryDocs MCP** or running a web search tool for content on **supermemory.ai/docs**.
+
+STEP 1: ASK ME THESE QUESTIONS
+
+1. What are you building?
+   - Personal chatbot/assistant
+   - Team knowledge base
+   - Customer support bot
+   - Document Q&A
+   - Other
+
+2. How do you want to integrate?
+   - Vercel AI SDK (@supermemory/tools)
+   - OpenAI plugins
+   - Direct SDK (supermemory npm/pip)
+   - Direct API calls
+
+3. Data model?
+   - Individual users only → containerTag: userId
+   - Organizations only → containerTag: orgId
+   - Both users AND orgs → ask for strategy
+
+4. Do you want USER PROFILES?
+   User profiles are automatically-maintained facts about users (what they like, what they're working on, preferences).
+   - Yes (RECOMMENDED) → Use client.profile() to get context
+   - No → Just use search
+
+5. How should I retrieve context?
+   - OPTION A: One call with search included → profile({ containerTag, q: userMessage })
+   - OPTION B: Separate calls → profile() for facts, search() for memories
+
+STEP 2: INSTALL
+
+# Get API key: https://console.supermemory.ai
+npm install supermemory  # or: pip install supermemory
+# For Vercel AI SDK: npm install @supermemory/tools
+export SUPERMEMORY_API_KEY="sm_..."
+
+
+STEP 3: CONFIGURE SETTINGS (DO THIS FIRST)
+
+typescript
+// PATCH https://api.supermemory.ai/v3/settings
+fetch('https://api.supermemory.ai/v3/settings', {
+  method: 'PATCH',
+  headers: { 'x-supermemory-api-key': process.env.SUPERMEMORY_API_KEY },
+  body: JSON.stringify({
+    shouldLLMFilter: true,
+    filterPrompt: `This is a [your app description]. containerTag is [userId/orgId]. We store [what data].`
+  })
+})
+
+STEP 4: CONTAINER TAG STRATEGY
+
+Based on their data model answer:
+
+USER-ONLY APP:
+typescript
+
+
+ORG-ONLY APP:
+typescript
+containerTag: orgId  // Org members share memories
+
+
+BOTH (ask which):
+- Option A: `containerTag: \`\${userId}-\${orgId}\``
+- Option B: `containerTag: orgId, metadata: { userId }`
+- Option C: `containerTag: userId, metadata: { orgId }`
+
+STEP 5: INTEGRATION CODE
+
+Based on their integration choice:
+
+--- VERCEL AI SDK ---
+
+typescript
+import { streamText } from 'ai'
+import { anthropic } from '@ai-sdk/anthropic'
+import { supermemoryTools } from '@supermemory/tools/ai-sdk'
+
+// Option 1: Agent tools (recommended for agentic flows)
+const result = await streamText({
+  model: anthropic('claude-3-5-sonnet-20241022'),
+  prompt: userMessage,
+  tools: supermemoryTools(process.env.SUPERMEMORY_API_KEY, {
+    containerTags: [userId]
+  })
+})
+// Agent gets searchMemories, addMemory, fetchMemory tools
+
+// Option 2: Profile middleware (automatic context injection)
+import { withSupermemory } from '@supermemory/tools/ai-sdk'
+const modelWithMemory = withSupermemory(anthropic('claude-3-5-sonnet-20241022'), userId)
+
+const result = await generateText({
+  model: modelWithMemory,
+  messages: [{ role: 'user', content: userMessage }]
+})
+// Profile is automatically injected into context
+
+
+--- DIRECT SDK (WITH PROFILES) ---
+
+typescript
+import Supermemory from 'supermemory'
+
+const client = new Supermemory()
+
+// Before each LLM call:
+const { profile, searchResults } = await client.profile({
+  containerTag: userId,
+  q: userMessage  // Include this if they chose OPTION A (one call)
+                  // Omit if they chose OPTION B (separate calls)
+})
+
+// Build context
+const context = `
+Static facts: ${profile.static.join('\n')}
+Recent context: ${profile.dynamic.join('\n')}
+${searchResults ? `Memories: ${searchResults.results.map(r => r.content).join('\n')}` : ''}
+`
+
+// Send to LLM
+const messages = [
+  { role: 'system', content: `User context:\n${context}` },
+  { role: 'user', content: userMessage }
+]
+
+// After LLM responds:
+await client.memories.add({
+  content: `user: ${userMessage}\nassistant: ${response}`,
+  containerTag: userId
+})
+
+
+--- DIRECT SDK (NO PROFILES) ---
+
+```typescript
+import Supermemory from 'supermemory'
+
+const client = new Supermemory()
+
+// Search for relevant memories
+const results = await client.search({
+  q: userMessage,
+  containerTag: userId,
+  searchMode: 'hybrid',  // Searches memories + document chunks
+  limit: 5
+})
+
+// Build context
+const context = results.results.map(r => r.content).join('\n')
+
+// Send to LLM with context
+const messages = [
+  { role: 'system', content: `Relevant context:\n${context}` },
+  { role: 'user', content: userMessage }
+]
+
+// Store the conversation
+await client.memories.add({
+  content: `user: ${userMessage}\nassistant: ${response}`,
+  containerTag: userId
+})
+
+--- PYTHON VERSION ---
+python
+from supermemory import Supermemory
+
+client = Supermemory()
+
+# With profiles (if they want it)
+profile_data = client.profile(
+    container_tag=user_id,
+    q=user_message  # Include if OPTION A, omit if OPTION B
+)
+
+context = f"""
+Static: {chr(10).join(profile_data.profile.static)}
+Dynamic: {chr(10).join(profile_data.profile.dynamic)}
+"""
+
+# Store conversation
+client.add(content=f"user: {user_message}\\nassistant: {response}", container_tag=user_id)
+
+--- DIRECT API ---
+
+bash
+# Add memory
+curl -X POST https://api.supermemory.ai/v3/documents \
+  -H "x-supermemory-api-key: $SUPERMEMORY_API_KEY" \
+  -d '{"content": "conversation", "containerTag": "userId"}'
+
+# Get profile
+curl -X POST https://api.supermemory.ai/v4/profile \
+  -H "x-supermemory-api-key: $SUPERMEMORY_API_KEY" \
+  -d '{"containerTag": "userId", "q": "search query"}'
+
+# Search
+curl -X POST https://api.supermemory.ai/v4/search \
+  -H "x-supermemory-api-key: $SUPERMEMORY_API_KEY" \
+  -d '{"q": "query", "containerTag": "userId", "searchMode": "hybrid"}'
+
+STEP 6: FILE UPLOADS (if they need it)
+
+typescript
+// Files are automatically extracted (PDFs, images with OCR, videos with transcription)
+const formData = new FormData()
+formData.append('file', fileBlob)
+formData.append('containerTag', userId)
+
+await fetch('https://api.supermemory.ai/v3/documents/file', {
+  method: 'POST',
+  headers: { 'x-supermemory-api-key': process.env.SUPERMEMORY_API_KEY },
+  body: formData
+})
+
+// Processing is async - check status before assuming searchable
+// GET /v3/documents/{documentId}
+
+
+STEP 7: SEARCH MODES
+
+typescript
+// HYBRID (recommended) - searches memories + document chunks
+searchMode: 'hybrid'
+
+// MEMORIES ONLY - just extracted memories, no original text
+searchMode: 'memories'
+
+
+STEP 8: METADATA FILTERS (if they need secondary filtering)
+
+typescript
+await client.search({
+  q: query,
+  containerTag: userId,
+  filters: {
+    AND: [
+      { key: 'type', value: 'conversation', type: 'string_equal' },
+      { key: 'timestamp', value: '2024', type: 'string_contains' }
+    ]
+  }
+})
+
+KEY POINTS:
+
+1. Configure settings FIRST with filterPrompt
+2. User profiles = automatic facts about users (profile.static + profile.dynamic)
+3. profile({ containerTag, q }) combines profile + search in ONE call
+4. Search modes: 'hybrid' (recommended) or 'memories'
+5. File extraction is automatic - no config needed
+6. Store conversations after each interaction
+7. containerTag should match what you put in filterPrompt
+
+TESTING:
+
+bash
+# 1. Configure settings
+curl -X PATCH https://api.supermemory.ai/v3/settings \
+  -H "x-supermemory-api-key: $SUPERMEMORY_API_KEY" \
+  -d '{"shouldLLMFilter": true, "filterPrompt": "..."}'
+
+# 2. Add test memory
+curl -X POST https://api.supermemory.ai/v3/documents \
+  -H "x-supermemory-api-key: $SUPERMEMORY_API_KEY" \
+  -d '{"content": "Test", "containerTag": "test_user"}'
+
+# 3. Get profile
+curl -X POST https://api.supermemory.ai/v4/profile \
+  -H "x-supermemory-api-key: $SUPERMEMORY_API_KEY" \
+  -d '{"containerTag": "test_user"}'
+
+
+NOW:
+1. Ask me the 5 questions above
+2. Generate complete working code based on my answers
+3. Include installation, settings config, and full integration
+
+DOCS: https://supermemory.ai/docs
+```
+</Accordion>
+
+
+
+---
+
+## Claude Code Skill
+
+Interactive setup for Claude Code users.
+
+### Install
+
+```bash
+# 1. Clone repo
+git clone https://github.com/supermemoryai/supermemory.git
+
+# 2. Copy skill
+mkdir -p ~/.claude/skills
+cp supermemory/.claude/skills/supermemory-integrate.md ~/.claude/skills/
+
+# 3. Restart Claude Code
+```
+
+### Use
+
+```bash
+/supermemory-integrate
+```
+
+The skill asks questions interactively and generates code for your specific setup.
+
+---
+
+## Next Steps
+
+<CardGroup cols={2}>
+  <Card title="Quickstart" icon="rocket" href="/quickstart">
+    Manual integration guide
+  </Card>
+
+  <Card title="User Profiles" icon="user" href="/user-profiles/overview">
+    Deep dive into profiles
+  </Card>
+
+  <Card title="Search API" icon="search" href="/search/overview">
+    Search modes and parameters
+  </Card>
+
+  <Card title="API Reference" icon="code" href="https://api.supermemory.ai/v3/openapi">
+    Complete API docs
+  </Card>
+</CardGroup>