by polterguy
Fully Autonomous AI-based Software Development Assistant
# Add to your Claude Code skills
git clone https://github.com/polterguy/magicmagic is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by polterguy. Fully Autonomous AI-based Software Development Assistant. It has 1,145 GitHub stars.
magic's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/polterguy/magic" and add it to your Claude Code skills directory (see the Installation section above).
magic is primarily written in C#. It is open-source under polterguy on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh magic against similar tools.
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Magic is an open-source, self-hostable AI software development platform that generates and runs full-stack business applications and AI agents from natural language.
Magic is built on top of OpenAI and Hyperlambda, a DSL specifically created to solve anything related to backend software development, and to be "The AI agent programming language". Create full stack apps, in an open source environment, resembling Lovable, Bolt, or Replit. Use natural language as input, and host it on your own hardware if you wish.
No additional "backend connectors" or "database connectors" required!
Hence, ZERO lockin!!
Everything is 100% integrated, thx to SQLite, with optional MySQL, PostgreSQL, and Microsoft SQL Server capabilities. Basically, run the whole shebang on your own hardware if you wish ...
Below is an app that was created with the following prompt;
Create me a full stack app to manage VIP customer for a car dealership
The whole process took about 30 minutes in total, with less than a handful of errors, correcting the LLM or giving feedback some 5 to 10 times during the process. All bugs were easily tracked down and eliminated by a seasoned software developer during the process.

Magic asked a handful of control questions, before it automatically generated the database, created the backend code based upon the integrated Hyperlambda Generator, before finally assembling the frontend based upon the API - Complete with authentication and authorization, 100% secure (of course!) Everything deployed locally, on the integrated and built-in webserver.
Once you save the code, you can test it! No "deployment" or "publish" required to test code!
Below is the AI agent in Magic 100% autonomously browsing the web and filling out a "contact us" form. This particular example is using the integrated headless browser, that allows your AI agent to "see" the web, autonomously browse it, and solve tasks.

However, you can also vibe code AI agents integrated with your CRM system, ERP system, legacy databases, "whatever". Magic fundamentally is an AI agent, for building software and AI agents. What you use it for, is up to you.
In addition to the AI agent in its dashboard, that generates entire full stack apps using nothing but natural language input - There's a whole range of additional components in the system allowing you to automate software development, such as for instance;
Below is a screenshot from Hyper IDE.

The above illustrates how Magic facilitates for "comment driven development", as in provide "natural language instructions" with a declarative comment, and have the system implement the code using the built-in AI code generator.
Magic is also a web server, allowing you to instantly deploy everything, without compilation, build processes, complex pipeline connectors, etc. So the process is as follows;
... or use the integrated headless browser to automatically generate AI workflows that tests your system automatically once done!
This comes in stark contrast to other less sophisticated tools, such as Lovable and Bolt44 that requires you to deploy into 2 different 3rd party providers before you can even test your code. Hence, the development model in Magic is probably for most practical concerns roughly 10x faster and more optimised ...
In addition to having the ability to generate pure JS, CSS, and HTML frontends, that's immediately being served, without any deployment pipelines - The system also comes with several pre-built frontend systems out of the box, such as the AI Expert System, which allows you to serve password protected AI agents, and/or for that matter deliver entire SaaS AI solutions.
The system is particularly well suited for creating AI agents.
Magic comes with MCP support out of the box. Install the plugin called "mcp", and configure Claude Cowork/Code or OpenAI's Codex to use Magic cloud as an MCP server, and Claude/Codex is automagically extended with all HTTP endpoint files you've got in your "modules" folder.
Magic contains a headless browser, PuppeteerSharp specifically, that allows you to browse the web as a human being, fill out forms, click buttons, etc.
You can see an example of that prompt in the screenshot below.

Contrary to other vibe coding tools, Magic Cloud was built for software developers from day 1. That means among other things it's got Git integrated as an integral part of the platform. This allows you to setup any amount of pipelines you wish, using Git for code, or GitHub workflows for deployments.
Below is how the integrated AI agents objectively compares Magic Cloud to Lovable and Bolt44.

Generate and execute Python scripts on the fly, and have the LLM use these as "tools". In addition, you can use BASH and the underlying terminal, and you can create Hyperlambda extension keywords using C#.
Since Magic is running in a protected service account by default, this is actually quite safe - However, obviously do not open up endpoints allowing 3rd party users to generate and execute arbitrary Python code.
You can also persist Python scripts, and reference these later as "tools", permanently widening the capabilities of AI agents, or for that matter integrate Python execution into your endpoints and services.

NOTICE - You obviously have to be logged in as root to generate and execute both Python scripts, Terminal scripts, and to create C# extensions. Magic has a unique security model however, that eliminates entire axioms of security-related "holes". But you still need to keep your brain. Magic is not (pun!) a "magic pill".
If you choose to create AI agents instead of full stack app, something the system is particularly well suited for, you can choose to deliver these as password protected AI expert systems, or embeddable AI chatbots, embedded on some website. Below is our AI chatbot. You can try it here

When we measure Hyperlambda and Magic Cloud, it's roughly around 20 times faster than similar solutions built in Python, such as Fast API or Flask. Compared to LangChain, it's probably around 50 times faster, in addition to making it much easier to create workflows, due to being able to create backend code using English, instead of "drag and drop WYWIWYG hell". Hyperlambda solutions are in general on pair with C# combined with Entity Framework, both on scalabaility and performance. Below is Hyperlambda versus Fast API and Flask.

Magic Cloud is built in C# and .Net Core 10.
On average, Magic is probably around 100 to 1,000 times faster than "graphical workflow solutions", such as N8N, LangChain, Zapier, Make, etc - Due to relying upon an actual programming language instead of JSON, XML, or Markdown based "workflow files". Executing a piece of Hyperlambda is around 1,000 times faster than parsing "dynamic logic" from YAMNL or JSON files.
Hyperlambda is almost on pair with pure C# code!
The easiest way to get started is to use Docker and create a "docker-compose.yaml" file with the following content;
version: "3.8"
services:
backend:
image: servergardens/magic-backend:latest
platform: linux/amd64
container_name: magic_backend
restart: unless-stopped
ports:
- "4444:4444"
volumes:
- magic_files_etc:/magic/files/etc
- magic_files_data:/magic/files/data
- magic_files_config:/magic/files/config
- magic_files_modules:/magic/files/modules
frontend:
image: servergardens/magic-frontend:latest
container_name: magic_frontend
restart: unless-stopped
depends_on:
- backend
ports:
- "5555:80"
volumes:
magic_files_etc: