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I built a persistent memory API for AI agents — and it's ...
Nadeem Shaikh · 2026-06-18 · via DEV Community

Nadeem Shaikh

Every AI agent has the same problem.

The moment a session ends, everything is gone. No memory of the
user. No context from last week. No continuity. Every conversation
starts from zero.

I built AgentMemo to fix this.

What is AgentMemo?

AgentMemo is a REST API that gives AI agents persistent memory.
Agents can store memories, retrieve them semantically, and forget
them when needed.

The key word is semantically. Not keyword search.
Meaning-based search.

Store: "The customer prefers email over phone and is on the Pro plan."

Query: "How should we contact this user?"

Result: ✅ Returns the memory with score 0.62 — zero keyword overlap,
pure semantic understanding.

Two lines to get started

Get a free API key instantly — no credit card, no email required:

# Get your API key
curl -X POST https://agentmemo.dev/signup \
  -H "Content-Type: application/json" \
  -d '{"name":"my-agent"}'

# Store a memory
curl -X POST https://agentmemo.dev/memory/store \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "user_id": "user_123",
    "agent_id": "support_bot",
    "content": "User prefers dark mode and works in TypeScript",
    "metadata": {"plan": "pro"}
  }'

# Retrieve relevant memories semantically
curl "https://agentmemo.dev/memory/retrieve?user_id=user_123&query=what+does+this+user+prefer" \
  -H "Authorization: Bearer YOUR_KEY"

What makes it different

Semantic search — memories retrieved by meaning not keywords.
Built on vector embeddings generated automatically on every store.

Agent-native signup — agents can self-register via POST /signup
with zero human involvement. No email. No verification. Key returned
instantly in JSON.

MCP server — works natively with Claude, Cursor, and any MCP
client. Add it in two lines:

{
  "mcpServers": {
    "agentmemo": {
      "url": "https://agentmemo.dev/mcp",
      "transport": "streamable-http",
      "headers": {
        "Authorization": "Bearer YOUR_KEY"
      }
    }
  }
}

auth.md support — AgentMemo publishes an auth.md file at
agentmemo.dev/auth.md so any auth.md-compatible agent can
discover and self-register automatically.

TTL support — set expiry on memories. Weather from yesterday?
Expires in 24 hours. User preferences? Keep forever.

Namespaces — organize memories by project, session, or topic.
Isolated memory spaces within one API key.

Edge deployed — sub-50ms globally. No cold starts.
No servers to manage.

Inject memories into any LLM

The most powerful use case — building the context window:

// Get API key from signup
const key = "am_sk_your_key";

// Before calling Claude/GPT, fetch relevant memories
const res = await fetch(
  `https://agentmemo.dev/memory/retrieve?user_id=${userId}&query=${currentMessage}`,
  { headers: { Authorization: `Bearer ${key}` } }
);
const { memories } = await res.json();

// Inject into system prompt
const systemPrompt = `
You are a helpful assistant.

What you remember about this user:
${memories.map(m => `- ${m.content}`).join('\n')}

Use this context to give personalized responses.
`;

// Now call Claude/GPT with full context
const response = await anthropic.messages.create({
  model: "claude-sonnet-4-6",
  system: systemPrompt,
  messages: [{ role: "user", content: currentMessage }]
});

// Store what happened for next time
await fetch("https://agentmemo.dev/memory/store", {
  method: "POST",
  headers: { 
    Authorization: `Bearer ${key}`,
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    user_id: userId,
    agent_id: "assistant",
    content: `User asked: ${currentMessage}. Key outcome: ${summary}`
  })
});

Why I built this

I believe the next generation of software won't be used by humans —
it will be run by agents.

And every agent needs a memory.

The big AI labs are building memory inside their own walls.
Claude remembers — but only within Anthropic. GPT remembers —
but only within OpenAI.

Nobody was building the memory layer that works across ALL of them.

AgentMemo is that layer.

Try it

🔗 Live: https://agentmemo.dev
📖 Docs: https://agentmemo.dev/docs
🔌 MCP: https://agentmemo.dev/mcp.json
🤖 auth.md: https://agentmemo.dev/auth.md

Free during beta. No limits. No credit card.

Would love your feedback — especially if you're building
multi-agent systems. What memory features would make your
agents smarter?