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.

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: 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" 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: js // 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 https://agentmemo.dev 📖 Docs: https://agentmemo.dev/docs https://agentmemo.dev/docs 🔌 MCP: https://agentmemo.dev/mcp.json https://agentmemo.dev/mcp.json 🤖 auth.md: https://agentmemo.dev/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?