Building a Cursor‑like AI Native IDE with OpenSumi and CodeFuse – A Step‑by‑Step Guide

Cursor (https://www.cursor.com) has become a breakout AI‑powered IDE, overtaking GitHub Copilot in popularity. Backed by Anysphere, which recently raised a $60 million Series A round led by OpenAI, Cursor demonstrates how deep focus on user value can achieve product‑market fit.

Key success factors of Cursor are its early access to the most advanced large‑language models (GPT‑4 in Dec 2022, later Claude Sonnet 3.5) and a series of model‑level optimisations such as repository‑wide embeddings and speculative decoding that push output speed to ~1 000 tokens / s. These innovations enable features like multi‑line completion, intelligent rewrite, next‑token prediction, and an Inline Chat that lets developers generate or modify code directly inside the editor.

The article then analyses why many other AI‑assisted development tools (GitHub Copilot, Amazon CodeWhisperer, Sourcegraph Cody, etc.) cannot match Cursor’s capabilities. Plugin‑based assistants are limited by the VS Code/JetBrains extension APIs: they can offer code completion and basic chat, but they cannot provide true multi‑line completion or the seamless Inline Chat experience that Cursor delivers.

A comparison table (AI IDE vs. plugin) highlights the functional gaps:

功能项

AI IDE 可以做

插件可以做

仓库级补全

✅

✅

多行补全

✅

❌

智能改写

✅

⚠️（通过 Decoration 实现但易溢出）

下一次补全预测

✅

✅

编辑器内通过自然语言生成代码

✅

❌

编辑器内快速问答

✅

❌

智能终端

✅

❌

AI Lint

✅

❌

聊天面板

✅

✅

Because plugin APIs are inherently restrictive, many companies consider forking VS Code to create a custom AI IDE. However, this approach introduces three major problems:

Upgrade difficulty – deep forks diverge from upstream, making future updates costly.

High maintenance overhead – VS Code was not designed for heavy customisation.

Potential defects – new bugs can appear in the forked codebase.

OpenSumi (https://github.com/opensumi/core) offers a better solution. It is an open‑source, high‑performance, highly extensible IDE framework that supports both web and Electron targets. Its main characteristics are:

Modular development – >50 atomic IDE modules that can be freely combined.

High extensibility – dependency‑injection allows swapping core implementations.

Multi‑platform support – desktop, Cloud IDE, remote, and container‑less modes.

VS Code plugin compatibility – third‑party extensions work out of the box.

In May 2024 OpenSumi released version 3.0 with AI‑enhanced core panels. Building on this, Ant Group’s CodeFuse IDE (https://github.com/codefuse-ai/codefuse-ide) is an open‑source desktop AI IDE built on OpenSumi. CodeFuse adopts a production‑ready module layout (browser, node, common) and provides a complete Electron‑based development pipeline (build, package, auto‑update).

Step‑by‑step guide to create your own Cursor‑like AI IDE

1️⃣ Preparation

• Node.js ≥ 20 • Yarn as the package manager • Access to an LLM that follows the ChatGPT API (e.g., Ollama, DeepSeek, OpenAI). You will need the model endpoint and an API key.

2️⃣ Fork & clone CodeFuse IDE and install dependencies

git clone [email protected]:codefuse-ai/codefuse-ide.git && cd codefuse-ide
# Use npmmirror for faster installs in China
yarn config set -H npmRegistryServer "https://registry.npmmirror.com"
export ELECTRON_MIRROR=https://npmmirror.com/mirrors/electron/
# Install dependencies
yarn
# Rebuild native Electron modules
yarn run electron-rebuild

3️⃣ Modify the AI model configuration

The default model settings live in src/ai/browser/ai-model.contribution.ts . Replace the placeholder values with your own endpoint, API key, and model names. Example (using a local Ollama server):

ai.model.baseUrl = "http://127.0.0.1:11434/v1";
ai.model.apiKey = "YOUR_API_KEY";
ai.model.chatModelName = "deepseek-coder";
ai.model.chatMaxTokens = 1024;
ai.model.chatTemperature = 0.2;

A full list of configurable fields (baseUrl, apiKey, chatModelName, chatSystemPrompt, chatMaxTokens, chatTemperature, chatPresencePenalty, chatFrequencyPenalty, chatTopP, codeModelName, codeSystemPrompt, codeMaxTokens, codeTemperature, etc.) is shown in the table below:

配置项

说明

默认值

ai.model.baseUrl

API URL 前缀，兼容 ChatGPT 格式

http://127.0.0.1:11434/v1

ai.model.apiKey

API Key

-

ai.model.chatModelName

对话模型名称

-

ai.model.chatMaxTokens

对话模型最大生成 token 数量

1024

ai.model.chatTemperature

对话模型采样温度

0.2

ai.model.chatPresencePenalty

presence_penalty 参数

1.0

ai.model.chatFrequencyPenalty

frequency_penalty 参数

1.0

ai.model.chatTopP

采样温度的替代方案

-

ai.model.codeModelName

补全模型名称（未填则与对话模型相同）

-

ai.model.codeMaxTokens

补全模型最大生成 token 数量

64

ai.model.codeTemperature

补全模型采样温度

0.2

Beyond model configuration, you can customise the product name, icon, and even implement OAuth login by extending OpenSumi modules (see src/ai/browser/ai-native.contribution.ts and the OpenSumi AI integration docs).

4️⃣ Run the IDE

yarn start

The IDE launches with all OpenSumi AI features (inline chat, multi‑line completion, smart rewrite, AI‑powered terminal, etc.).

To package the application for distribution, use yarn package to create an Electron app and yarn make for signed installers (macOS notarisation required).

Vision

In the era of rapidly advancing large‑model capabilities, plugin‑centric AI assistance will hit a ceiling. A true AI‑native IDE, built on an extensible framework like OpenSumi, is the optimal path for startups and enterprises that want to deliver the full power of generative AI to developers.