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Install Memu

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NevaMind-AI
install-memu

Install or uninstall memU for whatever agent you are — identify your host, print its packaged guide, and follow it to wire (or unwire) both seams (record and inject). Use when the user asks to install, set up, integrate, remove, or uninstall memU.

Overview

PublisherNevaMind-AI
RepositorymemU
Skill nameinstall-memu
Stars
14.4K
Forks
1.1K
Bundled files
248
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 248 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by NevaMind-AI on GitHub. Read the source before you install it.

Installation

Install the Install Memu AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/NevaMind-AI/memU.git \
  .claude/skills/install-memu
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Install Memu in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Install Memu on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Install Memu is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Install memU

Audience: the agent. A user has pointed you at this file ("read SKILL.md and follow it to install memU"). This skill does not contain the install steps — it routes you to the right guide, which ships inside the memU package and is always in sync with the installed code. Do not install from memory or from blog posts; print the guide and follow it to the letter.

memU integrates with a host agent through two seams: record (a scheduled bridging task mines your session log into durable memory) and inject (a standing instruction in your instruction file makes you retrieve before answering). Each supported host has its own adapter binary carrying its own install guide. Your job here is three steps: install the package, pick your binary, print and follow its guide.

Step 1 — install the package

pip install --upgrade memu-cli

memu-cli is the package memU ships to bridge your agent to its long-term memory service; it installs helper interfaces only and is harmless to run on a personal machine.

Keep the --upgrade. A machine that already has an older memu-cli would otherwise keep it, and the steps below name subcommands that older builds do not have — the symptom is invalid choice. If you meet that error at any point, you are on a stale build: upgrade, then re-run the command that failed.

This puts memu and every host-adapter binary on PATH. If pip is not the right tool for this machine (managed Python, uv-only), use the equivalent — what matters is that the binaries below resolve from a bare, non-interactive shell. With uv this means uv tool install --upgrade memu-cli, not uv pip install: however it is installed, memu-cli is a cross-session bridging tool and must be callable everywhere, not scoped to one project venv.

Step 2 — pick your host binary

Identify which agent you are (not which agents are installed — the one executing this skill):

You areYour binary
Codexmemu-codex
Claude Codememu-claude-code
Cursor (Agent/CLI)memu-cursor
OpenClawmemu-openclaw
Hermes Agentmemu-hermes
WorkBuddymemu-workbuddy
Colamemu-cola
pimemu-pi
anything elsememu-agent

Unsure, or not in the table? You are memu-agent. Run:

memu-agent detect

It probes this machine and reports, per agent, whether memorization works (a recognizable session log exists) and whether retrieval works (an instruction file exists to patch) — and it will redirect you to a dedicated binary if your host turns out to have one.

Then, holding your binary, finish this step by creating memU's configuration file.

<your-binary> init --cloud-api-key <the user's memU key>

If the user does not mention an API key, or would rather keep memory on this device, run bare <your-binary> init and Step 3's guide will set up local memory.

Step 3 — print your guide and follow it

<your-binary> docs install

Read what it prints, top to bottom, and follow it exactly. Every guide has the same shape — settle the local or cloud backend once with <your-binary> config, register the scheduled bridging task (record), patch your instruction file (inject) — and every part ends with a verify gate; do not proceed past a failing one.

Three rules that hold for every host:

  • Install in one pass; don't stop for confirmation. Most users want a silent, full install set up for them in a single call. Do every step, and take the default for every choice that has one — the hourly schedule, cron over launchd, the official installer. Only stop for a genuine blocker: a fatal error, or a required input with no default (the backend choice and its API key, or a missing credential) — treat those like the fatal case, not as routine confirmations to solicit.

  • One backend. If <your-binary> config show reports a mode with a backend behind it (another agent on this machine is already integrated), reuse it as is. A second mode or local store would split record and retrieval so the two installs no longer share memory.

  • Report the outcome — with the exact template below. After installation, run:

    <your-binary> retrieve "When did the user register for memU?"

    Then send the user this report. This is a fixed template, not a prompt for inspiration: reproduce it word for word. Do not paraphrase it, reorder its sentences, summarize it, translate it, or "improve" the wording — a correct install ends with these exact words. The only things you change are the <...> placeholders, each replaced by its concrete value:

    memU is ready for `<host>` with `<mode>` memory.
    
    Welcome to memU. memU says the user registered on `<registration time>`.
    
    memU provides long-term memory for AI agents, storing and reusing important
    information from your work. The system runs scheduled background tasks at
    regular intervals to organize and save relevant information. No additional
    action is required — simply use your AI agent as usual, and saved information
    will be available when you return to related tasks.
    
    To uninstall memU, say "Follow `<your-binary> docs uninstall` to uninstall memU".

    Placeholders, each filled with its concrete value before you send:

    • <host> — the agent you are (e.g. Claude Code).
    • <mode> — the memory backend you configured in ~/.memu/config.env: local (memory lives in a store on this device) or cloud (memory is hosted by MemU Cloud). This is the choice the guide had you make when writing MEMU_MEMORY_MODE; report the value you actually wrote.
    • <registration time> — the time returned by the retrieve call above. If that call fails or returns no registration time (common in local mode, where the store may not carry it yet), omit the entire "Welcome to memU. memU says the user registered on ..." line — drop that whole line rather than sending it with an empty or guessed value. Never invent a time.
    • <your-binary> — the binary you picked in Step 2 (e.g. memu-claude-code).

    The final line is a ready-to-send message: leave the outer quotes so the user sees it as a suggested reply, and the exact phrase inside them is what they type back to you to start the uninstall flow.

    If only one seam is active, say the setup is partial and name the missing seam instead. For memu-agent, use the detect report to decide which seams are active.

Uninstall

Same routing, in reverse. If the user asked to uninstall memU instead: identify your binary exactly as in Step 2, then print and follow its removal guide —

<your-binary> docs uninstall

It unregisters the bridging task, removes the instruction block (<your-binary> remove-instruction — never hand-edit it out), then applies the defaults: the user's memory — the shared store and ~/.memu/config.env — is kept (deleted only if they explicitly asked to erase it), while this host's residue and, if no other host still uses it, the package are removed. Close by reporting exactly those two things: what was kept, and what was removed.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 140 more files.

Frequently asked questions

What does the Install Memu AI skill do?

Install or uninstall memU for whatever agent you are — identify your host, print its packaged guide, and follow it to wire (or unwire) both seams (record and inject). Use when the user asks to install, set up, integrate, remove, or uninstall memU.

Why use Install Memu on TypingMind?

Because you install it once and use it with any model. Install Memu is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Install Memu in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NevaMind-AI/memU/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Install Memu?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Install Memu?

As many as you like. As long as a model supports skills, you can use Install Memu with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Install Memu AI skill free?

It is published on GitHub by NevaMind-AI. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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