Vercel AI SDK

Use Supermemory with Vercel AI SDK for seamless memory management

The Supermemory AI SDK provides native integration with Vercel’s AI SDK through two approaches: User Profiles for automatic personalization and Memory Tools for agent-based interactions.

@supermemory/tools on npm

Check out the NPM page for more details

Installation

npm install @supermemory/tools

Quick Comparison

Approach	Use Case	Setup
User Profiles	Personalized LLM responses with automatic user context	Simple middleware
Memory Tools	AI agents that need explicit memory control	Tool definitions

---

User Profiles with Middleware

Automatically inject user profiles into every LLM call for instant personalization.

import { generateText } from "ai"
import { withSupermemory } from "@supermemory/tools/ai-sdk"
import { openai } from "@ai-sdk/openai"

const modelWithMemory = withSupermemory(openai("gpt-5"), "user-123")

const result = await generateText({
  model: modelWithMemory,
  messages: [{ role: "user", content: "What do you know about me?" }]
})

Memory saving is disabled by default. The middleware only retrieves existing memories. To automatically save new memories:

const modelWithMemory = withSupermemory(openai("gpt-5"), "user-123", {
  addMemory: "always"
})

Memory Search Modes

Profile Mode (Default) - Retrieves the user’s complete profile:

const model = withSupermemory(openai("gpt-4"), "user-123", { mode: "profile" })

Query Mode - Searches memories based on the user’s message:

const model = withSupermemory(openai("gpt-4"), "user-123", { mode: "query" })

Full Mode - Combines profile AND query-based search:

const model = withSupermemory(openai("gpt-4"), "user-123", { mode: "full" })

Custom Prompt Templates

Customize how memories are formatted:

import { withSupermemory, type MemoryPromptData } from "@supermemory/tools/ai-sdk"

const claudePrompt = (data: MemoryPromptData) => `
<context>
  <user_profile>
    ${data.userMemories}
  </user_profile>
  <relevant_memories>
    ${data.generalSearchMemories}
  </relevant_memories>
</context>
`.trim()

const model = withSupermemory(anthropic("claude-3-sonnet"), "user-123", {
  mode: "full",
  promptTemplate: claudePrompt
})

Verbose Logging

const model = withSupermemory(openai("gpt-4"), "user-123", {
  verbose: true
})
// Console output shows memory retrieval details

---

Memory Tools

Add memory capabilities to AI agents with search, add, and fetch operations.

import { streamText } from "ai"
import { createAnthropic } from "@ai-sdk/anthropic"
import { supermemoryTools } from "@supermemory/tools/ai-sdk"

const anthropic = createAnthropic({ apiKey: "YOUR_ANTHROPIC_KEY" })

const result = await streamText({
  model: anthropic("claude-3-sonnet"),
  prompt: "Remember that my name is Alice",
  tools: supermemoryTools("YOUR_SUPERMEMORY_KEY")
})

Available Tools

Search Memories - Semantic search through user memories:

const result = await streamText({
  model: openai("gpt-5"),
  prompt: "What are my dietary preferences?",
  tools: supermemoryTools("API_KEY")
})
// AI will call: searchMemories({ informationToGet: "dietary preferences" })

Add Memory - Store new information:

const result = await streamText({
  model: anthropic("claude-3-sonnet"),
  prompt: "Remember that I'm allergic to peanuts",
  tools: supermemoryTools("API_KEY")
})
// AI will call: addMemory({ memory: "User is allergic to peanuts" })

Fetch Memory - Retrieve specific memory by ID:

const result = await streamText({
  model: openai("gpt-5"),
  prompt: "Get the details of memory abc123",
  tools: supermemoryTools("API_KEY")
})

Using Individual Tools

For more control, import tools separately:

import {
  searchMemoriesTool,
  addMemoryTool,
  fetchMemoryTool
} from "@supermemory/tools/ai-sdk"

const result = await streamText({
  model: openai("gpt-5"),
  prompt: "What do you know about me?",
  tools: {
    searchMemories: searchMemoriesTool("API_KEY", { projectId: "personal" }),
    createEvent: yourCustomTool,
  }
})

Tool Results

// searchMemories result
{ success: true, results: [...], count: 5 }

// addMemory result
{ success: true, memory: { id: "mem_123", ... } }

// fetchMemory result
{ success: true, memory: { id: "mem_123", content: "...", ... } }