Rememberall
wrannaman · Coding · Leaning
Rememberall is an open-source AI memory tool. It gives GPTs and AI apps persistent memory across chats, backed by a self-hosted REST API.
About Rememberall
What Is Rememberall
Rememberall is a long-term memory layer for AI applications. It stores facts and context from past conversations, then pulls the relevant ones back when a user asks about them. The problem it targets is simple and annoying: most chatbots forget everything the moment a session ends, so every follow-up starts from zero and you end up repeating yourself in every single new chat.
The core idea is a memory store you own. Instead of trusting a vendor with your conversation history, you run Rememberall yourself and it keeps the data. Memories go in through a REST API, get indexed for semantic search, and come back out ranked by meaning rather than exact keyword match. When you ask "what did we decide about auth last week," the store can surface a note saved as "JWT tokens with a 24-hour expiry." That's the payoff.
Rememberall was built for GPT Store builders and AI developers. You add it to a custom GPT with an OpenAPI spec and mention @rememberall in conversation to save or recall context. Developers can also call the API directly. The honest limits: it's a young project, its last code push was January 2025, and the self-hosted setup assumes you're comfortable with Docker.
Getting Started
- For GPT builders, install Rememberall from the GPT Store and add it to your custom GPT's configuration using the provided OpenAPI spec.
- Mention @rememberall in your GPT conversation to store information or recall past context.
- For developers, clone the repository and deploy the stack with Docker Compose from the deploy folder.
- Authenticate your requests with a Bearer token, since every endpoint requires it.
- Use the API to write memories with POST /memory and search them with GET /memories, or manage everything from the dashboard.
Product Information
A quick look at Rememberall's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- GPT Store builders
- AI developers and tinkerers
- Privacy-conscious teams
Tasks
- Storing conversation context
- Recalling past discussions
- Managing saved memories
- Wiring memory into a GPT
Scenarios
- A support GPT that needs to remember a customer's setup and past tickets across separate chats.
- A research assistant that should recall earlier findings without you pasting them again.
- A personal assistant that tracks ongoing projects and picks up where you left off.
Key features
Persistent memory across conversations
Rememberall keeps context alive after a chat ends. Store a fact in one session, ask about it in the next, and it comes back. Simple. That's the whole reason the tool exists, and it fixes the most common complaint about GPTs: the amnesia that resets every conversation the moment you close the tab.
Semantic search over stored memories
Memories are indexed and searched by meaning, not exact wording. The README example has a user ask about authentication decisions made last week, and the tool surfaces the note about JWT-based auth. You get relevant hits even when your query shares no words with what was saved. Why does that matter? Because exact keyword search fails the moment you phrase a question differently, and that happens constantly in real conversations.
Vector-based storage
The memory store uses vector storage to power that search. Vectors let the system compare the meaning of a query against everything saved, so a large history stays searchable instead of turning into a pile of text you scroll through by hand. No manual filing. The README says the vector store is self-hosted rather than rented.
Self-hosted and privacy-first deployment
You run Rememberall yourself with Docker Compose, so conversation data stays on your infrastructure. The project lists end-to-end encryption, fine-grained access control, and GDPR-compliant data handling. This is the feature that separates it from hosted memory add-ons. It's also the one that adds setup work. You trade convenience for control.
Simple REST API
Two endpoints cover the basics: POST /memory to write a memory and GET /memories to list or search them, with limit and offset for paging. Every request needs a Bearer token. Easy enough. For developers, that's a low bar to clear. You can wire it into a GPT, a script, or a custom app.
OpenAPI spec for GPT integration
For GPT builders, the integration path is a config change, not a coding project. You point your custom GPT at the included OpenAPI spec, and the GPT gains memory abilities. Then @rememberall in the conversation triggers a save or a recall. Quick to set up. It keeps the flow conversational, which is exactly where memory needs to live.
Dashboard for memory management
The project ships a dashboard where you can view and manage what's been stored. It matters. Memory you can't inspect is memory you can't trust, and the dashboard turns the store from a black box into something you can audit and prune.
Open source and extensible
The code is open, so you can read it, fork it, and change how memory works to fit your use case. Not locked down. For a memory layer that touches sensitive conversations, being able to inspect the implementation is more than a nice-to-have.
Pros and cons
Pros
- Solves the GPT forgetfulness problem directly: memories persist across separate conversations.
- Self-hosting keeps conversation data on your own infrastructure instead of a vendor's.
- Semantic search returns relevant memories even when your query words differ from what was saved.
- The REST API and OpenAPI spec make integration realistic for both builders and developers.
- Open source means you can audit and customize the memory logic, which matters for sensitive data.
Cons
- Self-hosting shifts the ops burden to you, so you'll need Docker skills, a server to run it on, and a plan for updates and backups.
- The project is young and its last repository push was January 2025, so expect a small community and slow-moving docs.
- There's no published pricing because there's no hosted plan; you bring your own infrastructure and its costs.
- Setup for GPT builders involves editing config with an OpenAPI spec, which will frustrate anyone who wanted a one-click install.
Frequently asked questions
It gives AI apps and custom GPTs long-term memory. Rather than forgetting a conversation when the session ends, Rememberall saves context to a store and retrieves it later, so the AI can recall past discussions, preferences, and decisions in future chats.
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