Detailed Introduction
Osaurus is a macOS-focused LLM server and developer toolkit that lets developers and creators run models locally or in the cloud with OpenAI / Anthropic-compatible APIs. It provides an MCP (Model Context Protocol) server for integration with clients like Cursor and Claude Desktop, and includes a menu bar chat, plugins, and developer tools for embedding model capabilities into the desktop ecosystem securely and with low latency.
Main Features
- OpenAI and Anthropic compatible API layer for easy integration with existing tools and clients.
- MCP server to enable context sharing and plugin extensions with desktop clients such as Cursor and Claude Desktop.
- Native Apple Silicon support and local model execution to reduce latency and improve privacy.
- Menu bar chat, plugin system, and developer tools for debugging and extension.
Use Cases
- Run local or on-device models on macOS for privacy-first inference and testing.
- Provide a compatible model backend and MCP interface for desktop apps, enabling plugin-driven workflows.
- Use as a local OpenAI/Anthropic-compatible endpoint in development and CI for offline testing and integration.
Technical Details
Osaurus is implemented with Swift and the native macOS stack, designed as a developer-friendly inference and integration platform. Repository topics include mcp, llm, and apple-neural-engine. The project is released under the MIT License and targets scenarios requiring local model deployment, low-latency inference, and desktop integration.