Cursor AI Persistent Memory:
Give Cursor a Brain That Survives Every Session

The problem: Cursor starts from zero, every time

You spend the first 10–20 minutes of every Cursor session re-explaining your project: the tech stack, the constraints, the bugs you just fixed, the naming conventions your team agreed on last week. This is not Cursor's fault — it has no state between sessions. But it is your problem, and it compounds every day.

A senior developer in a mature codebase wastes 30–45 minutes per day on this re-briefing. Over a year, that's more than 150 hours — nearly four full work weeks — just to put the AI back where you left it.

The solution: cachly — persistent memory for Cursor via MCP

cachly is the persistent memory layer for AI coding assistants. It integrates with Cursor via the Model Context Protocol (MCP) — Cursor's standard extension interface — and provides 121 tools that give Cursor long-term memory, causal reasoning, and failure prediction.

The core loop is simple: cachly captures lessons from every session and every git commit, stores them in a knowledge graph with causal edges, and injects a concise briefing at the start of each new Cursor session. Cursor arrives knowing your stack, your recent bugs, and what the team learned yesterday.

Setup: one command, under 2 minutes

npx @cachly-dev/mcp-server@latest autopilot

The wizard detects Cursor automatically, writes the MCP config to~/.cursor/mcp.json, and authenticates you with a single browser click. No API keys in config files. No YAML to hand-edit. Done.

Then it runs brain_from_git — reading your entire git history and extracting lessons from every bug fix, revert, and architecture decision your team has ever made. Cursor knows years of context before the first new line is written.

What the Cursor MCP config looks like

// ~/.cursor/mcp.json (auto-written by setup)
{
  "mcpServers": {
    "cachly": {
      "command": "npx",
      "args": ["@cachly-dev/mcp-server@latest", "start"],
      "env": {
        "CACHLY_INSTANCE_ID": "your-instance-id"
      }
    }
  }
}

You can also add this manually if you prefer, then paste your instance ID from the cachly dashboard. But the setup wizard is faster.

What Cursor can do with cachly memory

Session briefing — zero typing required

Every Cursor session starts with session_start — automatically called at the first tool use. cachly sends back a structured briefing: your recent work, open bugs, team lessons, and your latest memory crystal (a compressed wisdom snapshot). Cursor reads the full context before you type a word.

Instant root-cause analysis

Describe a bug in plain language: causal_trace("payment webhook 500 on retry"). cachly searches the causal knowledge graph — thousands of causally-linked events from your git history — and returns the root cause, the failure chain, the exact fix that resolved it before, and who committed it. No more 30-minutegit blame spelunking.

Failure prediction before deploy

Before pushing to production, call brain_predict. cachly scans your brain for recurring failure patterns and returns weighted warnings about what is likely to break — ranked by confidence, backed by your own historical data. Not generic advice. Predictions specific to your codebase.

Automatic learning from commits

The setup installs a git post-commit hook. Every commit you make is automatically sent to cachly via learn_from_attempts. Bug fixes, reverts, refactors — all become lessons in the brain. Cursor's memory grows with every line of code your team writes, without any manual effort.

cachly vs Cursor's built-in context window

Does cachly work with Cursor Rules?

Yes — they're complementary. Cursor Rules (.cursorrules) are great for static, project-specific coding standards. cachly is for dynamic, session-aware memory: what broke last week, what the team decided yesterday, what patterns predict failures in your specific codebase.

Many developers use both: Cursor Rules for stable conventions, cachly for living institutional memory. You can even have cachly write relevant patterns into your Cursor Rules automatically via the export_rules tool.

GDPR, privacy, and data residency

cachly runs on Hetzner servers in Nuremberg, Germany — inside the EU. All data stays in the EU. There is no PII extraction from your code or commit messages beyond what you explicitly teach the brain. GDPR-native by design.

Prefer full control? cachly supports BYOC (Bring Your Own Cache) — run the full stack on your own infrastructure with one Docker command. Air-gapped, no external calls.

Get started in 2 minutes

# Install and configure cachly for Cursor
npx @cachly-dev/mcp-server@latest autopilot

# In any Cursor session, verify it works:
# cachly will call session_start automatically
# and Cursor will receive your full briefing

The free tier includes unlimited sessions, 5,000 lessons, and all 115 MCP tools. No credit card. No expiry. Upgrade when you need team Brain or higher limits.