osaurus
Runs AI agents locally on macOS without cloud dependency, giving you full data privacy and control over model execution.
A native macOS app (built in Swift for Apple Silicon) that runs AI agents locally with persistent memory, tool execution, and autonomous task running. It works fully offline with local models, can connect to cloud providers, and exposes OpenAI-, Anthropic-, and Ollama-compatible APIs plus an MCP server so other tools can use it as a local backend. MIT licensed.
- Local code analysis and refactoring without sending source to external APIs
- Autonomous task execution with memory across multiple invocations
- Privacy-critical agent workflows in regulated industries
Runs AI agents locally on macOS without cloud dependency, giving you full data privacy and control over model execution. Persistent memory and cryptographic identity enable stateful, verifiable autonomous workflows.
Teams needing on-device AI agent automation with strict data residency requirements or offline capability.
https://github.com/osaurus-ai/osaurus
By osaurus-ai
How to Get It
brew install --cask osaurus
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After installing, paste this into Claude:
Help me local code analysis and refactoring without sending source to external APIs
Trust Signals Auto-scanned
Community Pulse Active
Discussed on Hacker News, Reddit
- Brisket-osaurus — Reddit · 1280 pts
- I call it Billy and the Clone-Osaurus — Reddit · 923 pts
- WHAT I’VE ALWAYS WANTED— WRITE THE GREAT AMERICAN NOVEL. MINE IS ABOUT A FUTURIS — Reddit · 788 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
catalog_hygiene stale-eval refresh: Scored from trust signals (evidence-eval-v1): 7,591 GitHub stars; 35 contributors; last commit 7d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
catalog_hygiene stale-eval refresh: Scored from trust signals (evidence-eval-v1): 7,591 GitHub stars; 35 contributors; last commit 7d ago; license MIT.