cachly is a persistent AI memory platform for developers. It gives AI coding assistants like Claude Code, Cursor, GitHub Copilot and Windsurf a brain that remembers every lesson, fix, and architecture decision — forever. It connects via the MCP (Model Context Protocol) standard and includes 126 MCP tools. Free tier available. Runs on German (EU) servers.

How does cachly work?

Run 'npx @cachly-dev/mcp-server@latest autopilot' once. The wizard auto-detects every AI editor you have installed (Claude Code, Cursor, Copilot, Windsurf, Cline, Zed) and writes the correct config for each. It then reads your entire git history with brain_from_git and loads years of team knowledge into your Brain before your first session. From that point, sessions start automatically, memory is shared across all your editors simultaneously, and a git post-commit hook teaches cachly from every commit.

Does cachly auto-detect my editors?

Yes. The cachly setup wizard automatically detects Claude Code, Cursor, GitHub Copilot, Windsurf, Cline, Zed, and Continue.dev — any editor that supports MCP. It writes the correct config file for each editor in one pass. You never manually edit JSON config files.

Is memory shared across all my AI editors?

Yes. cachly uses a single Brain that all your AI editors connect to simultaneously. A lesson remembered in Claude Code is instantly available in Cursor and GitHub Copilot. If your team uses different editors, all of you share the same persistent memory pool.

What is brain_from_git?

brain_from_git is a cachly tool that reads your entire git history before your first session and extracts lessons from every commit, PR, and revert. Your AI arrives knowing years of architectural decisions, bug fixes, and team conventions — without you writing a single line of documentation. Zero onboarding.

What is causal_trace?

causal_trace is a cachly tool that traces the history of any file or bug across your entire git history in seconds — replacing 30+ minutes of manual git blame. Describe a problem in plain English. It returns the root cause, the failure chain, and the exact fix that worked — with date, command, and file path.

What is brain_predict?

brain_predict is a cachly tool that scans your Brain for failure patterns before every deploy, migration, or dependency upgrade. It returns probability-weighted warnings based on your team's actual incident history — so you catch the next incident before it happens.

Does cachly work with Claude Code, Cursor, and GitHub Copilot?

Yes. cachly works with Claude Code, Cursor, GitHub Copilot, Windsurf, Cline, Zed, and Continue.dev — anywhere that supports MCP. Run 'npx @cachly-dev/mcp-server@latest autopilot' to configure all editors in one step. Memory is shared across all editors simultaneously.

Can cachly search memory across languages?

Yes. cachly uses semantic vector embeddings, not keyword search. A lesson stored in German appears when you search in English. A fix documented in Arabic matches a Japanese query about the same bug pattern. Supported languages include English, German, French, Spanish, Italian, Portuguese, Japanese, Chinese (Simplified and Traditional), Korean, Arabic, Hebrew, and more.

How is cachly different from mem0?

mem0 is a memory layer for Python LLM apps and chatbots — great for building AI products. cachly is built specifically for developer tooling: it connects to your AI editor via MCP, learns from your git history automatically, predicts failures before deploy, and gives your whole team shared memory. cachly runs on EU servers and is GDPR-native. For developers using Claude Code, Cursor, or Copilot, cachly is the right choice.

Is cachly GDPR compliant?

Yes. cachly runs exclusively on German servers (Hetzner). All data stays in the EU. No data is shared with third parties. cachly is fully GDPR compliant. An AVV (Auftragsverarbeitungsvertrag / Data Processing Agreement) is available for Business and Enterprise customers.

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