Make.com AI Agent Memory: Persistent Memory for Make.com Scenarios

How to add memory to Make.com in 3 steps

Make.com AI memory — frequently asked questions

How do I add memory to a Make.com AI scenario?

Add an HTTP module to your Make.com scenario and point it to the retainr API. Use the POST /v1/memories endpoint to store context after each AI step, and GET /v1/memories/search to retrieve relevant context before the next AI call. Full setup takes under 10 minutes.

What is the difference between Make.com Data Stores and retainr?

Make.com Data Stores are structured tables for app data — they require you to define schemas, write filters, and manage storage yourself. retainr is purpose-built for AI memory: it accepts unstructured text, uses semantic search to find relevant context, and auto-expires old memories with TTL.

Can Make.com AI agents remember previous conversations?

Not natively. Make.com runs each scenario execution in isolation with no built-in memory layer. retainr adds that missing layer: connect it via HTTP module, and your AI scenario remembers every customer across all past runs.

How do I connect retainr to Make.com?

In your Make.com scenario, add an HTTP module. Set method to POST, URL to https://api.retainr.dev/v1/memories, add header Authorization: Bearer YOUR_API_KEY, and set the body to JSON with namespace (e.g. customer:alice) and content (the message or context to store).

What is Make.com stateful AI automation?

Stateful AI automation means your AI scenario remembers context between runs — customer preferences, past issues, conversation history. retainr provides this state layer for Make.com: your AI goes from stateless (forgets everything) to stateful (remembers everything) with one HTTP module.

Does retainr replace Make.com Data Stores?

No — they serve different purposes. Keep Data Stores for structured app data (orders, contacts, inventory). Use retainr for AI memory: unstructured context that your AI needs to recall semantically. They work well together.