osaurus

🥇Gold

Osaurus is an AI edge infrastructure for macOS that enables operations teams to run local or cloud models. It shares tools across apps via MCP and powers AI workflows with a native, always-on runtime. Integrates with Anthropic, Apple Foundation Models, and OpenAI.

11280Updated Today

Intermediate30min to implementautomation

Saves ~150 min per use

Quick InstallView Source

git clone https://github.com/dinoki-ai/osaurus.git

Works with:

Claude

Overview

About This Skill

https://docs.osaurus.ai/

Use Cases

Automate the execution of AI tasks on a schedule, such as generating reports or processing data.

Integrate multiple AI models from different providers into a single workflow for enhanced capabilities.

Create custom AI personas with unique prompts and tools for specific applications or user interactions.

Utilize voice input features to transcribe and interact with applications hands-free.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/dinoki-ai/osaurus

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Using Osaurus, can you help me automate a workflow for [COMPANY] in the [INDUSTRY] industry to enhance productivity? I want to run a local AI model that analyzes [DATA] and shares insights across applications using MCP.

Example Output

### Automated Workflow Insights for Acme Corp

**Industry:** Marketing  
**Data Analyzed:** Customer Engagement Metrics  

**Overview:**  
Using Osaurus, we automated the analysis of customer engagement metrics for Acme Corp, allowing for real-time insights across various applications. The local AI model processed data from social media, email campaigns, and website interactions.  

**Key Findings:**  
- **Engagement Rate:** Increased by 25% over the last quarter.  
- **Top Performing Channels:** Social media platforms led to a 40% higher conversion rate compared to email.  
- **Recommendations:** Focus on enhancing content for social media and consider A/B testing for email campaigns to boost performance.  

**Conclusion:**  
This automation not only saved time but provided actionable insights that can drive future marketing strategies.