magic
polterguy · polterguy/magic
Công cụ này tạo ra các ứng dụng full-stack và tác nhân AI an toàn, tức thì từ ngôn ngữ tiếng Anh đơn giản, chạy trên phần cứng của bạn và hoạt động như một MCP server để lộ các endpoint cho các tác nhân như Claude và Cursor.
Instant SECURE Full Stack Apps and AI Agents
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Ảnh từ README của tác giả polterguy ·Nguồn
Bạn có thể làm gì với nó
- Tạo một hệ thống CRM full-stack an toàn từ mô tả ngôn ngữ tự nhiên, bao gồm cơ sở dữ liệu, API và giao diện người dùng.
- Tạo các tác nhân AI điều khiển bằng cơ sở dữ liệu có thể truy vấn và cập nhật cơ sở dữ liệu tùy chỉnh của bạn thông qua một API bảo mật.
- Lộ các endpoint API của ứng dụng của bạn làm công cụ cho Claude hoặc Cursor, cho phép các tác nhân tương tác với các dịch vụ của bạn một cách lập trình.
Kiểm tra an toàn
Không thấy dấu hiệu rủi ro trong các file đã quét.
Quét tự động các file trong repo. Luôn xem lại code trước khi chạy.
Trích từ README
Instant SECURE Full Stack Apps and AI Agents
Turn plain English into a working full-stack app — database, secure API, business logic, and frontend — running on your own hardware, with zero lock-in. An open-source alternative to Lovable, Bolt, and Replit that gives you the whole backend, plus an MCP server that turns every endpoint into a tool for Claude, Cursor, or Codex. Read more about Hyperlambda.
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Run it in 60 seconds
curl -fsSL https://hyperlambda.dev/docker-compose.yaml | docker compose -f - up
Then open localhost:5555, point it at localhost:4444, and log in with root / root.
Point the API Wizard at your database, and it generates a complete, secured REST API — then extend it in plain English, without a build or deploy step.
⭐ If this saves you time, star the repo — it's the main way other developers find it.
What you can build
- Full-stack business apps — CRM systems, admin panels, booking systems, internal tools; database, secure API and frontend generated from natural language
- Database-driven AI agents — agents that query and update your database and invoke your endpoints, behind your own role-based access control
- AI chatbots and expert systems — crawl a website, get an embeddable chatbot grounded in your own content
- Secure APIs over legacy databases — point it at an existing MySQL, PostgreSQL, SQL Server or MariaDB schema and get a CRUD API in seconds
- Wrappers around third-party APIs — paste an OpenAPI or Swagger URL and get typed, documented endpoints wrapping Stripe, GitHub, Slack or anything else publishing a spec
- MCP tool servers — expose your endpoints to Claude, Cursor, Codex, Qoder or any MCP client
- Background jobs and automation — scheduled tasks written in Hyperlambda, or generated from a plain English description
- Static sites and SPAs — your cloudlet serves files directly, next to the APIs powering them
How it compares
| Magic Cloud | Lovable / Bolt | n8n / Zapier / Make | |
|---|---|---|---|
| License | MIT, fully open source | Proprietary | Mixed |
| Self-hostable | Yes — your hardware, your data | No | Partly |
| Backend included | Database, API, auth, RBAC, jobs | Frontend + third-party BaaS | Workflows only |
| Deploy step before you can test | None — save and run | Deploy to third parties first | Publish step |
| Execution model | Compiled .NET runtime | — | Interprets JSON/YAML workflows |
| MCP server | Built in | No | No |
| Vendor lock-in | None | Yes | Yes |
The LLM that cannot hallucinate functions
Magic runs Hyperlambda, which can be generated by our own proprietary LLM. Because we generate an AST rather than text, the output is analysed and rejected if it contains functions that don't exist. The Hyperlambda Generator cannot return hallucinated function invocations — like any LLM it can still write logically wrong code, but every function it invokes is guaranteed to exist.
Combined with the ability to restrict the vocabulary, this lets you ship AI agents that grow their own tool space on demand, without widening your attack surface.
Unique security model
Hyperlambda runs sandboxed, with no file system access outside its sandbox, and can whitelist individual functions through its RBAC system — so your server can accept code as input and execute it safely without knowing where it came from. Restricting invocations at the execution level makes Hyperlambda, as far as we know, the only language that currently does this.
I'm so confident in the codebase quality, I'll give you $100 if you can find a severe security-related bug in its backend code — and another $100 if you can exploit the natural language API, which has accepted arbitrary public input for 3 months with nobody succeeding.
MCP support — and an 80% token saving
Install the mcp plugin, point Claude Code, Cowork, or OpenAI's Codex at your cloudlet, and every HTTP endpoint in your modules folder becomes a tool the agent can invoke. In our measurements this also cuts token consumption by roughly 80%. Calculate your own savings here.
Performance
In our measurements Hyperlambda is roughly 20× faster than FastAPI or Flask, around 50× faster than LangChain, and 100–1,000× faster than graphical workflow tools such as n8n, Zapier and Make — because it runs a real compiled runtime instead of interpreting logic out of JSON, XML or YAML. Hyperlambda solutions are broadly on par with C# and Entity Framework on both performance and scalability.
The dashboard
The sidebar is the whole platform: Hyper IDE for editing, running and replaying any file on the server, Playground for executing Hyperlambda without saving it first, SQL Studio for querying and designing databases, Endpoint Generator for turning tables into secured CRUD endpoints, wrapping caller-supplied code in a role-scoped sandbox, and importing third-party APIs from their OpenAPI specifications, plus users and roles, scheduled tasks, machine learning, and the plugin store.
Your cloudlet is also an AI agent. With the MCP plugin installed, the URL at the top hands any MCP-capable agent your endpoints as tools. The Chatbot Wizard goes the other way: give it a website, and it crawls the site, turns what it finds into training data, and hands you an embeddable chatbot grounded in your own content.
Once you save the code, you can test it — no deployment or publish step required.
Notice the prompt bar below the editor, where "the Machine Creates the Code". Describe what you want in plain English and the built-in generator writes it straight into the file you're editing. The same bar follows you into the Playground and SQL Studio, generating Hyperlambda, SQL, HTML, or whatever fits the file you have open.


