by isair
Private local AI assistant for your desktop. Voice and text chat, personal memory, dictation and MCP tools. Runs offline with Ollama or OpenAI-compatible servers on macOS, Windows and Linux.
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# Add to your Claude Code skills
git clone https://github.com/isair/jarvisGuides for using ai agents skills like jarvis.
Last scanned: 10/14/2026
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A private, local-first voice assistant that lives on your computer. Talk naturally, as if Jarvis were a third person in the room.
Voice-first · Local AI · Personal memory · No subscription
Download Jarvis → · Get started · Explore the app · Support the project
Jarvis is built to be part of the conversation. Talk through an idea, discuss plans with a friend, then ask “Jarvis, what do you think?” While listening, it keeps a short, temporary rolling transcript of nearby speech so it can join an ongoing conversation using what was just discussed.
Address Jarvis by name anywhere in a sentence and follow up naturally. Speech recognition, language models and speech synthesis run on hardware you control.
Your conversation and all data stays solely on your computer. Sensitive information is redacted before it reaches model context or the saved diary, even though both are local, to ensure the security of your private information. Web search, weather and connected tools use the network but send only what is necessary when you ask for those capabilities.
1. Download the app. Choose your platform from GitHub Releases.
| Platform | Package | Open |
|---|---|---|
| macOS · Apple Silicon | Jarvis-macOS-arm64.zip |
Extract, move to Applications, then right-click → Open |
| macOS · Intel | Jarvis-macOS-x64.zip |
Extract, move to Applications, then right-click → Open |
| Windows · x64 | Jarvis-Windows-x64.zip |
Extract, then run Jarvis.exe |
| Linux · x64 | Jarvis-Linux-x64.tar.gz |
Extract, then run ./Jarvis/Jarvis |
2. Choose your local models. The setup wizard guides you through speech recognition and a model server. Use Ollama, or connect an OpenAI-compatible server you already run, such as LM Studio, oMLX or llama.cpp.
3. Make it yours. Allow microphone access and let the first model downloads finish. When Jarvis reports that it is listening, try:
“Jarvis, help me think through my day.”
Right-click the face or use the tray menu to open Chat. Text replies are silent.
Memory needs depend on model size, quantisation, context length and speech recognition. Both Ollama and OpenAI-compatible setup show a memory budget; you can edit estimates for models served through an OpenAI-compatible endpoint. Smaller models trade capability for lower resource use.
| Starting point | Chat model |
|---|---|
| Smaller hardware | qwen3.5:0.8b |
| Constrained memory | gemma4:e2b |
| Default | gemma4:e4b |
| Larger local setup | qwen3.8:27b |
Budget memory for Whisper and, when different from chat, the fast model used for voice intent and tool routing. Apple Silicon uses unified memory; other GPUs use dedicated VRAM. Setup budgets chat and fast together alongside the selected Whisper model, using E2B for fast tasks when it fits or sharing E4B across both roles to save memory. Apple Silicon estimates reserve memory for macOS. Saved model choices are preserved, and insufficient memory shows CPU fallback guidance.
You: We could have a picnic tomorrow.
A friend: Depends on the weather. Should we plan something indoors instead?
You: Jarvis, what do you think?
Jarvis can use the recent conversation to understand that you are asking about the weather for the picnic, rather than treating the last sentence as an isolated question. This is the experience it is built around. Personalised requests can also draw on saved conversation history when no external tools are needed. How reliably it understands the context depends on speech recognition and your chosen model; see the evaluation results.
Keep setup, activity and settings within reach.
Choose the runtime that fits your machine. Setup walks through local models, speech and optional capabilities without requiring you to edit a configuration file.
The activity timeline keeps ordinary events readable. Downloads have a separate card with transferred bytes, percentage, speed and remaining time when the downloader provides them. Loading and warmup are distinct stages.
Choose models, tune speech recognition, configure tools and enable Low Power Mode from Settings in the tray menu.
Open Chat for silent replies in the same conversation. Pause Voice Listening stops room transcription during meetings while chat and dictation stay available.
Jarvis is developed primarily on macOS. Windows and Linux behaviour may differ. See the evaluation results for tested capabilities.
Most people can use Settings from the tray. Advanced setups can edit ~/.config/jarvis/config.json.
Open the configuration guide →
The guide covers local model servers, speech recognition, Low Power Mode, voices, dictation, location, MCP integrations and troubleshooting.
| Platform | Default hotkey |
|---|---|
| Windows | Ctrl + Win |
| macOS, where supported | Ctrl + Option |
| Linux | Ctrl + Alt |
Hold to record and release to paste. Double-tap for hands-free recording. Optional filler-word removal, a custom dictionary and dictation history are available in Settings. macOS needs Accessibility permission; Linux requires X11, with limited Wayland support.
Connect MCP servers for browser automation, Home Assistant, GitHub, databases and more. Credentials and network access depend on the tools you choose. Review a server's permissions before enabling it.
Integration examples and server settings →
🔇 Speech output unavailable: A voice-model or dependency failure disables speech output for the current run. Check the reason in Logs, correct the voice model settings or missing dependencies, then restart Jarvis.
🔊 Piper download interruptions: Connection resets and timeouts receive bounded retries. If they persist, check connectivity and restart Jarvis; completed voice files are retained. Certificate errors require correcting the trust configuration.
📥 Whisper download failures: Faster-whisper downloads run in a separate process with a five-minute limit. If a download crashes or times out, restart Jarvis to resume it; cached models stay available offline.
🎤 Whisper cache errors: Jarvis attempts one clean download recovery per startup. If it fails, check connectivity and free disk space, then follow the printed cache guidance and restart. Device fallbacks retain files downloaded during recovery.
Select an available microphone in Jarvis Settings, or set a default recording input in your system Settings, then restart Jarvis. Jarvis keeps the selected input t
jarvis is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by isair. Private local AI assistant for your desktop. Voice and text chat, personal memory, dictation and MCP tools. Runs offline with Ollama or OpenAI-compatible servers on macOS, Windows and Linux. It has 2,053 GitHub stars.
Yes. jarvis passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/isair/jarvis" and add it to your Claude Code skills directory (see the Installation section above).
jarvis is primarily written in Python. It is open-source under isair on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh jarvis against similar tools.
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