Claude has a native memory tool that allows it to store and retrieve information across conversations. Supermemory provides a backend implementation that maps Claude’s memory commands to persistent storage.
This integration works with Claude’s built-in memory tool type, introduced in the Anthropic API. It requires the context-management beta flag.
Installation
npm install @supermemory/tools @anthropic-ai/sdk
Quick Start
import Anthropic from "@anthropic-ai/sdk"
import { createClaudeMemoryTool } from "@supermemory/tools/claude-memory"
const anthropic = new Anthropic()
const memoryTool = createClaudeMemoryTool(process.env.SUPERMEMORY_API_KEY!, {
projectId: "my-app",
})
async function chatWithMemory(userMessage: string) {
// Send message to Claude with memory tool
const response = await anthropic.beta.messages.create({
model: "claude-sonnet-4-5",
max_tokens: 2048,
messages: [{ role: "user", content: userMessage }],
tools: [{ type: "memory_20250818", name: "memory" }],
betas: ["context-management-2025-06-27"],
})
// Handle any memory tool calls
const toolResults = []
for (const block of response.content) {
if (block.type === "tool_use" && block.name === "memory") {
const toolResult = await memoryTool.handleCommandForToolResult(
block.input as any,
block.id
)
toolResults.push(toolResult)
}
}
// Send tool results back to Claude if needed
if (toolResults.length > 0) {
const finalResponse = await anthropic.beta.messages.create({
model: "claude-sonnet-4-5",
max_tokens: 2048,
messages: [
{ role: "user", content: userMessage },
{ role: "assistant", content: response.content },
{ role: "user", content: toolResults },
],
tools: [{ type: "memory_20250818", name: "memory" }],
betas: ["context-management-2025-06-27"],
})
return finalResponse
}
return response
}
// Example usage
const response = await chatWithMemory(
"Remember that I prefer React with TypeScript for my projects"
)
console.log(response.content[0])
Configuration
import { createClaudeMemoryTool } from "@supermemory/tools/claude-memory"
const memoryTool = createClaudeMemoryTool(process.env.SUPERMEMORY_API_KEY!, {
// Scope memories to a project or user
projectId: "my-app",
// Or use container tags for more flexibility
containerTags: ["user-123", "project-alpha"],
// Custom memory container prefix (default: "claude_memory")
memoryContainerTag: "my_memory_prefix",
// Custom API endpoint
baseUrl: "https://custom.api.com",
})
How It Works
Claude’s memory tool uses a file-system metaphor. Supermemory maps these operations to document storage:
| Claude Command | Supermemory Action |
|---|
view | Search/retrieve documents |
create | Add new document |
str_replace | Update document content |
insert | Insert content at line |
delete | Delete document |
rename | Move document to new path |
Memory Path Structure
All memory paths must start with /memories/:
/memories/preferences.txt # User preferences
/memories/projects/react.txt # Project-specific notes
/memories/context/current.txt # Current context
Commands Reference
View (Read/List)
// List directory contents
{ command: "view", path: "/memories/" }
// Read file contents
{ command: "view", path: "/memories/preferences.txt" }
// Read specific lines
{ command: "view", path: "/memories/notes.txt", view_range: [1, 10] }
Create
{
command: "create",
path: "/memories/preferences.txt",
file_text: "User prefers dark mode\nFavorite language: TypeScript"
}
String Replace
{
command: "str_replace",
path: "/memories/preferences.txt",
old_str: "dark mode",
new_str: "light mode"
}
Insert
{
command: "insert",
path: "/memories/notes.txt",
insert_line: 5,
insert_text: "New note added here"
}
Delete
{ command: "delete", path: "/memories/old-notes.txt" }
Rename
{
command: "rename",
path: "/memories/old-name.txt",
new_path: "/memories/new-name.txt"
}
Complete Example
import Anthropic from "@anthropic-ai/sdk"
import { createClaudeMemoryTool } from "@supermemory/tools/claude-memory"
const anthropic = new Anthropic()
const memoryTool = createClaudeMemoryTool(process.env.SUPERMEMORY_API_KEY!, {
projectId: "assistant",
})
async function runConversation() {
const messages: Anthropic.MessageParam[] = []
// Helper to chat with memory
async function chat(userMessage: string) {
messages.push({ role: "user", content: userMessage })
let response = await anthropic.beta.messages.create({
model: "claude-sonnet-4-5",
max_tokens: 2048,
messages,
tools: [{ type: "memory_20250818", name: "memory" }],
betas: ["context-management-2025-06-27"],
})
// Handle tool calls
while (response.stop_reason === "tool_use") {
const toolResults = []
for (const block of response.content) {
if (block.type === "tool_use" && block.name === "memory") {
const result = await memoryTool.handleCommandForToolResult(
block.input as any,
block.id
)
toolResults.push(result)
}
}
messages.push({ role: "assistant", content: response.content })
messages.push({ role: "user", content: toolResults })
response = await anthropic.beta.messages.create({
model: "claude-sonnet-4-5",
max_tokens: 2048,
messages,
tools: [{ type: "memory_20250818", name: "memory" }],
betas: ["context-management-2025-06-27"],
})
}
messages.push({ role: "assistant", content: response.content })
return response
}
// Have a conversation with persistent memory
await chat("My name is Alex and I'm a backend developer")
await chat("I prefer Go for systems programming")
await chat("What do you remember about me?")
}
runConversation()
Environment Variables
SUPERMEMORY_API_KEY=your_supermemory_key
ANTHROPIC_API_KEY=your_anthropic_key
Next Steps
