Best AI Memory for Cursor (2026)
Cursor's Composer is great inside one project and amnesiac across them. Six ways to give Cursor persistent memory — including the .cursorrules baseline, the chat-history baseline, and a one-config-block hosted layer — evaluated honestly.
The quick answer
If you want persistent memory that drops into Cursor in 60 seconds and gives you a browsable wiki of what it remembered: Ricord. If you only ever work in one repo and like writing your own rules: .cursorrules. If you're building agents on top of Cursor as a coding environment: Letta. The matrix below spells out the rest.
Why this matters for Cursor specifically
Cursor's Composer is the strongest in-editor agent experience shipping today. Inside a single Composer session, it stitches together file edits, terminal output, and chat context cleanly. The break shows up at the seams: across Composer sessions, across projects, across days. Cursor doesn't remember the architectural decision you made yesterday, the API contract you negotiated with your backend team, or the deploy step that broke last week.
The fixes cluster into six approaches. They differ on six axes — install effort, project portability, auto-extraction, wiki browsability, conflict resolution, and cost. The right answer is a function of how you use Cursor day-to-day, not a single winner.
The decision matrix
Eight criteria, six options. Rows sorted by what Cursor users hit first (install effort) through what bites later (conflict resolution, cross-project portability).
| Criterion | Ricord | Mem0 | Letta | Supermemory | .cursorrules | Composer |
|---|---|---|---|---|---|---|
| MCP server install (one config block) | Limited | |||||
| Survives Composer session boundaries | ||||||
| Survives across separate projects/repos | Per-repo only | |||||
| Auto-extracts from your chats (no curation) | Manual | |||||
| Browsable wiki of what was learned | Raw markdown | Raw history | ||||
| Knowledge graph + backlinks | Pro only | |||||
| Conflict resolution (old facts superseded) | Basic | Manual edits | ||||
| Cost (smallest paid tier with memory) | $15/mo annual | $249/mo for graph | Self-host + LLM | $29/mo | $0 | $0 (built in) |
Slot-by-slot — which fits you
If you live in Cursor daily across multiple repos
Ricordis built for this — install once, every Cursor session writes to the same memory + wiki, scoped per project automatically. Cursor's MCP support picks it up without any per-project setup. The wiki view is the killer feature: by week two you can read what your AI has learned about each codebase you work on.
If you only work in one repo and you're a meticulous curator
A .cursorrules fileat your repo root is genuinely sufficient for this. You write the rules, Cursor follows them, no infra. The cost is curation — keeping it updated by hand and remembering to commit it. It doesn't auto-learn from your conversations, but for small static contexts that's fine.
If you're building an agent product, not just shipping code with Cursor
Lettaships an agent runtime with memory built in. If you're already writing agent orchestration code, the integrated model is cleaner than wiring memory as a separate service. If you just want memory for Cursor itself, Letta is overkill.
If you have engineering time to tune retrieval
Mem0open-source is the right pick. Apache-licensed, vector-first, forks cleanly. You'll spend real time getting it production-ready, but if memory retrieval isyour product's competitive edge, owning the code is the right trade. When OSS wins →
If Cursor is one of many AI surfaces you use
Supermemory ships a Chrome extension and Pipecat integration alongside its API. Strong choice when Cursor is just one slice of your AI workflow and you want memory that captures browser + audio context too.
If you're happy with whatever Composer remembers
Composer's built-in chat historycovers you for the current session and recent activity within the current project. If your work is mostly short loops and you never need to recall yesterday's context — fine. If you ever find yourself re-explaining the same thing in a new Composer chat, that's the signal you've outgrown it.
Why Ricord wins for most Cursor users
Three reasons, in order of how often we hear them from people who switched from .cursorrules or raw Composer:
- One install covers every project.No per-repo .cursorrules to maintain. Memory follows you across the four side projects, the day job, and the client work — scoped automatically so they don't leak into each other.
- The wiki view is browsable. Open the dashboard, read what Cursor learned about each codebase you work in. Not a search box on top of chat history — an actual document tree.
- Conflict resolution at ingest.When you change the deploy step or the API contract, Cursor doesn't remember both forever. Old facts get superseded, not stored alongside. This is what makes recall still useful at month three.
bun add -g ricord ricord login ricord install # auto-detects Cursor, Claude Code, Claude Desktop, Codex
Restart Cursor. Open Composer. Ask it to remember something. Ask again tomorrow in a different project. The wiki populates as you work.
Getting started
Pick the option that matches your slot. If it's Ricord, the three commands above get you running. If it's .cursorrules, just write the file. If it's OSS, fork Mem0 and start reading.
Either way, the signal that you picked right is whether you've stopped re-explaining the same context to Cursor after a week. If you haven't, your memory layer isn't doing its job — change something.