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[ARTICLE · art-32365] src=dev.to ↗ pub= topic=artificial-intelligence verified=true sentiment=↑ positive

I built a persistent memory API for AI agents — and it's free

A developer built AgentMemo, a free REST API that gives AI agents persistent, semantic memory. The API allows agents to store, retrieve, and forget memories based on meaning rather than keywords, and includes features like TTL support, namespaces, and MCP server compatibility. AgentMemo is designed to work across different AI models, providing a universal memory layer for agents.

read3 min views1 publishedJun 18, 2026

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.

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.

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

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

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"}
  }'

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

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.

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}`
  })
});

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.

🔗 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?

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