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<img width="2400" height="750" alt="image" src="https://github.com/user-attachments/assets/d3e36c98-4609-46d3-b39f-7ee1c6d77432" /> # decocms.com **decocms** is an open-source foundation for building AI-native software.\ We equip developers, engineers, and AI enthusiasts with robust tools to rapidly prototype, develop, and deploy AI-powered applications. **Official docs:** https://docs.deco.page > [!TIP] > If you have questions or want to learn more, please join our discord > community: https://decocms.com/discord ## Who is it for? - **Vibecoders** prototyping ideas - **Agentic engineers** deploying scalable, secure, and sustainable production systems ## Why deco CMS? Our goal is simple: empower teams with Generative AI by giving builders the tools to create AI applications that scale beyond the initial demo and into the thousands of users, securely and cost-effectively. <img width="1440" height="900" alt="image" src="https://assets.decocache.com/decochatweb/3c37a237-0c33-4db5-9cfd-a11ff084752a/decocx1.png" /> ## Core capabilities - **Open-source Runtime** – Easily compose tools, workflows, and views within a single codebase - **MCP Mesh (Model Context Protocol)** – Securely integrate models, data sources, and APIs, with observability and cost control - **Unified TypeScript Stack** – Combine backend logic and custom React/Tailwind frontends seamlessly using typed RPC - **Global, Modular Infrastructure** – Built on Cloudflare for low-latency, infinitely scalable deployments. Self-host with your Cloudflare API Key - **Visual Workspace** – Build agents, connect tools, manage permissions, and orchestrate everything built in code <img width="1440" height="900" alt="image" src="https://assets.decocache.com/decochatweb/2e6980db-296b-4972-b2d4-9f5265b6e74a/Usage-by-agent.png" /> --- ## Creating a new Deco project A Deco project extends a standard Cloudflare Worker with our building blocks and defaults for MCP servers.\ It runs a type-safe API out of the box and can also serve views — front-end apps deployed alongside the server. Currently, views can be any Vite app that outputs a static build. Soon, they’ll support components declared as tools, callable by app logic or LLMs.\ Views can call server-side tools via typed RPC. ### Requirements - Your preferred JavaScript runtime: - Recommended: [Bun](https://bun.sh) - Supported: [Node.js](https://nodejs.org), [Deno](https://deno.land) ### Quick Start 1. Create your project ``` npm create deco ``` or ``` bun create deco ``` > This will prompt you to log in or to create an account on > [decocms.com](https://decocms.com). 2. Enter the project directory and start the dev server ``` cd <my-project-directory> npm install npm run dev # → http://localhost:8787 (hot reload) ``` > Need pre‑built MCP integrations? Explore > [deco-cx/apps](https://github.com/deco-cx/apps). ## Project Layout ``` my-project/ ├── server/ # MCP tools & workflows (Cloudflare Workers) │ ├── main.ts │ ├── deco.gen.ts # Typed bindings (auto-generated) │ └── wrangler.toml ├── view/ # React + Tailwind UI (optional) │ └── src/ ├── package.json # Root workspace scripts └── README.md ``` > Skip `view/` if you don’t need a frontend. ## CLI Essentials | Command | Purpose | | --------------- | ---------------------------------------- | | `deco dev` | Run server & UI with hot reload | | `deco deploy` | Deploy to Cloudflare Workers | | `deco gen` | Generate types for external integrations | | `deco gen:self` | Generate types for your own tools | > For full command list: `deco --help` or see the > [CLI README](packages/cli/README.md) ## Building Blocks A Deco project is built using **tools** and **workflows** — the core primitives for connecting integrations, APIs, models, and business logic. ### Tools Atomic functions that call external APIs, databases, or AI models. All templates include the necessary imports from the Deco Workers runtime. ```ts import { createTool, Env, z } from "deco/mod.ts"; const createMyTool = (env: Env) => createTool({ id: "MY_TOOL", description: "Describe what it does", inputSchema: z.object({ query: z.string() }), outputSchema: z.object({ answer: z.string() }), execute: async ({ context }) => { const res = await env.OPENAI.CHAT_COMPLETIONS({ model: "gpt-4o", messages: [{ role: "user", content: context.query }], }); return { answer: res.choices[0].message.content }; }, }); ``` > Tools can be used independently or within workflows. **Golden rule:** one tool > call per step — keep logic in the workflow. --- ### Workflows Orchestrate tools using **Mastra** operators like `.then`, `.parallel`, `.branch`, and `.dountil`. > Tip: Add [Mastra docs](https://github.com/deco-cx/mastra) to your AI code > assistant for autocomplete and examples. ```ts import { createStepFromTool, createWorkflow } from "deco/mod.ts"; return createWorkflow({ id: "HELLO_WORLD", inputSchema: z.object({ name: z.string() }), outputSchema: z.object({ greeting: z.string() }), }) .then(createStepFromTool(createMyTool(env))) .map(({ inputData }) => ({ greeting: `Hello, ${inputData.answer}!` })) .commit(); ``` --- ### Views Build **React + Tailwind** frontends served by the same Cloudflare Worker. - Routing with [TanStack Router](https://tanstack.com/router) - Typed RPC via `@deco/workers-runtime/client` - Preconfigured with `shadcn/ui` and `lucide-react` --- ## Development Flow 1. Add an integration via the [decocms.com dashboard](https://decocms.com) _(improved UX coming soon)_ 2. Run `npm run gen` → updates `deco.gen.ts` with typed clients 3. Write tools in `server/main.ts` 4. Compose workflows using `.map`, `.branch`, `.parallel`, etc. 5. _(Optional)_ Run `npm run gen:self` → typed RPC clients for your tools 6. Build views in `/view` and call workflows via the typed client 7. Run locally ```bash npm run dev # → http://localhost:8787 ``` 8. Deploy to Cloudflare ```bash npm run deploy ``` --- ## How to Contribute (WIP) We welcome contributions! Check out [`CONTRIBUTING.md`](./CONTRIBUTING.md) for guidelines and tips. --- Made with ❤️ by the Deco community — helping teams build AI-native systems that scale.