core

🥇Gold

Core is a powerful framework designed for building AI Native IDE products quickly. It supports Model Context Protocol (MCP) tools through its MCP Client and Server, making it an essential tool for developers looking to integrate AI capabilities into their applications.

3,6054450Updated Today

Intermediate15 minutes to implementdevelopment

Saves ~360 min per use

Quick InstallView Source

claude install opensumi/core

Works with:

VS CodeGitHub Copilot

Overview

About This Skill

https://opensumi.com

Use Cases

Quickly build AI-driven IDEs that enhance coding efficiency.

Integrate MCP tools into existing applications for improved functionality.

Create custom development environments tailored to specific project needs.

Enhance code editing experiences with AI-powered features like auto-completion and error detection.

Best For

GrowthDevelopment

Setup & Installation

Quick Install

Terminal

claude install opensumi/core

Alternative Install (Git Clone)

git clone https://github.com/opensumi/core

Requirements

Claude Code or compatible AI agent
Works with: VS Code, GitHub Copilot

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

As a developer working with [COMPANY] in the [INDUSTRY], I want to quickly integrate AI capabilities into my application using the Core framework. Can you provide a step-by-step guide on how to use the Model Context Protocol (MCP) tools effectively?

Example Output

### Integrating AI with Core Framework

To integrate AI capabilities into your application using the Core framework, follow these steps:

1. **Set Up Your Environment**: Ensure you have the Core framework installed and configured in your development environment.
2. **Create an MCP Client**: Use the Core tools to create an MCP Client that connects to your AI model. This client will handle requests and responses between your application and the AI.
3. **Define Model Contexts**: Specify the contexts in which your AI model will operate. This includes defining input parameters and expected outputs.
4. **Test Your Integration**: Run tests to ensure that the MCP Client communicates correctly with the server. Validate that the AI responses meet your application's requirements.
5. **Deploy and Monitor**: Deploy your application and monitor the integration to ensure optimal performance and make adjustments as needed.

By following these steps, you can leverage the Core framework to build powerful AI-enhanced applications efficiently.