cachly vs mem0: experience for coding agents or memory for AI apps
Both keep memory for AI agents. mem0 is a memory layer you build into your own agents and apps, managed or self-hosted. cachly is made for coding agents: it keeps the lessons from fixes and decisions in your codebase.
This page compares both on facts you can check. Each row links its source.
At a glance
| Aspect | cachly | mem0 | Sources |
|---|---|---|---|
| What it is | cachlyExperience for coding agents. Your assistant stores a lesson after a fix and finds it again when the same problem returns. | mem0A memory layer for LLM agents: persistent context that survives across sessions. Two products: Mem0 Platform (managed) and Mem0 Open Source (self-hosted). | Sources |
| Built for | cachlyDevelopers who work with coding assistants. | mem0Teams that build AI agents and apps. SDKs for Python and JavaScript; memories are scoped by user, agent, app and session. | Sources |
| What gets stored | cachlyA lesson: topic, what worked, what failed, context, files and commands. Your assistant writes it, the Stop hook records reported fixes, and git history adds more. | mem0Memories that mem0 extracts from what your app or agent sends. The API adds, searches, lists, updates and deletes them, and shows each memory's history. | Sources |
| In Claude Code | cachlyA plugin with three hooks: SessionStart briefs the session, UserPromptSubmit adds matching lessons to every prompt, and Stop records reported fixes. | mem0A plugin. Hooks capture messages, answers, changed files and test results; a background worker extracts memories. Recall runs before the first answer of a session, for a first prompt of 20 characters or more. After that, through explicit search. | Sources |
| MCP server | cachlyAn MCP server on your machine. The editor lists 27 tools; 124 in total through one dispatcher tool. | mem0A hosted MCP server at mcp.mem0.ai; nothing runs on your machine. Sign-in through the browser or with an API key. | Sources |
| Coding tools | cachlyClaude Code as a plugin. Cursor, Windsurf, VS Code with GitHub Copilot, Cline, Continue.dev and Zed over MCP. A JetBrains plugin. | mem0Claude, Claude Code, Codex, Cursor, Windsurf, VS Code and OpenCode connect to the MCP server. | Sources |
| Where data lives | cachlyHosted by cachly: one instance per brain at Hetzner in Nuremberg, Germany. By default, cachly computes embeddings in the EU. The API runs behind Cloudflare, a US company. | mem0Mem0 Platform, run by Embedchain, Inc. (Mem0). Its privacy policy says some providers and its own operations are in the United States and other countries. | Sources |
| Run it yourself | cachlyHosted service. The MCP server and the hooks run on your machine and talk to your instance. | mem0Mem0 Open Source: the library, or a self-hosted server started with docker compose. Enterprise adds on-prem deployment of the Platform. | Sources |
| License | cachlyMCP server and hooks: Apache-2.0. The hosted service is closed source. | mem0Mem0 Open Source: Apache-2.0. Mem0 Platform is a managed service. | Sources |
| Pricing | cachlyFree €0: one brain, 25 MB, 500 recalls a month. Dev €19, Pro €49, Business €199 a month. Team: €49 a month for 5 seats. | mem0Hobby: free, 10,000 add and 1,000 retrieval requests a month, one project. Starter $19, Pro $249 a month. Enterprise: custom, with SSO, audit logs and on-prem deployment. | Sources |
| Community | cachlycachly-mcp: public repository since April 2026. | mem0Public on GitHub since June 2023, with a large open-source community. | Sources |
As of . Every statement about mem0 comes from the linked source, read on that day. Products change; if you spot something outdated, write to [email protected].
Both in Claude Code
Both ship a Claude Code plugin with hooks. The difference is when memory reaches the model. mem0 searches once, with the first prompt of a session, and adds up to five memories. Later questions go through an explicit search. cachly's UserPromptSubmit hook runs on every prompt and adds the lessons that match it.
They also differ in what they keep. mem0 captures the conversation and lets a model extract memories from it. cachly keeps lessons: what worked, what failed, the files and the commands, written by your assistant after a fix.
When to pick mem0
- You build an AI app or agent and want memory per user, agent, app or session through an SDK.
- You want memories extracted from conversations for you, by a model.
- You want to run it yourself: the open-source library or server, Apache-2.0.
- You want one memory for many MCP clients, from Claude to OpenCode.
When to pick cachly
- Your assistant writes code, and you want it to remember fixes, dead ends and the files involved.
- You want matching lessons next to every prompt, through a hook.
- Your data should be stored in Germany, with embeddings computed in the EU.
- A flat monthly price fits you: free with 500 recalls a month, or from €19 a month.
Try cachly
In Claude Code, cachly comes as a plugin with three hooks. Try it without an account: the first tool call creates a test brain on EU servers. The commands are in Hooks that carry experience.
For Cursor, Windsurf, VS Code and other editors, MCP integration shows the one-command setup. What leaves your machine, and where it lands: EU hosting and your data.
Sources
Other comparisons: cachly vs Supermemory · cachly vs Zep · cachly vs claude-mem · cachly vs Basic Memory · cachly vs Letta · All docs