Vercel AI SDK - Supermemory

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.

<Card title="@supermemory/tools on npm" icon="npm" href="https://www.npmjs.com/package/@supermemory/tools"> Check out the NPM page for more details </Card>

Installation

bash

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.

typescript

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?" }]
})

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

typescript

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

</Note>

Memory Search Modes

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

typescript

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

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

typescript

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

Full Mode - Combines profile AND query-based search:

typescript

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

Custom Prompt Templates

Customize how memories are formatted. The template receives userMemories, generalSearchMemories, and searchResults (raw array for filtering by metadata):

typescript

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

typescript

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.

typescript

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:

typescript

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:

typescript

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" })

Using Individual Tools

For more control, import tools separately:

typescript

import {
  searchMemoriesTool,
  addMemoryTool
} 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

typescript

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

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