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Делаем бесплатным вайб-кодинг: Пошаговая настройка Qwen CLI (MCP + Skills + Rules)

Main summary

Key takeaways

Technology

High-level purpose

This guide walks through installing and configuring the Qwen CLI (local agent/assistant) to perform automated, agent-driven “vibe-coding” (wipe-coding). The workflow:

  • Create a Next.js project from a written project spec.
  • Connect external tools (MCPs) and pre-written agent Skills.
  • Run and iterate the resulting app locally.

The demo used Qwen free model (Qwen 3.5+). The presenter stated roughly 2,000 free requests/day (can be increased by swapping accounts).

Key product and technology concepts

  • Qwen CLI: a command-line interface that runs a Qwen-based coding agent, configures UI/settings, creates projects, and runs agents that read project specs and act.
  • MCP (Machine Control Points): external connectors/servers the agent can use. Examples: Git providers, file system access, browser automation (Playwright), DB connectors, long-session memory, documentation providers. MCPs extend the agent’s capabilities (read/write repos, open pages, run automation, access docs).
  • Skills: packaged, pre-written prompts + instructions/examples that the agent can use as capabilities (for example, React/Next helper skills). Stored in a /skills folder as skill.md files and loaded by Qwen.
  • Project spec & Steps: project.md (Markdown project specification) and steps.md (step-by-step roadmap) that the agent reads to implement the project iteratively.
  • Prompt engineering / meta-prompts: a “prompt-for-prompts” file that asks structured questions so the agent can generate a refined prompt tailored to your app (frameworks, UI style, features).

Prerequisites

  • Node.js (use the latest version).
  • A terminal (Windows/Mac) and a code editor (Visual Studio Code recommended).
  • Qwen CLI installation command (copied from Qwen docs / CLI page).
  • Authentication via the Qwen chat web page (confirm/create account after installing the CLI).

Installation & initial setup

  1. Install Node.js (latest).
  2. Install Qwen CLI (run the install command from Qwen CLI docs in your terminal).
  3. Authenticate: run the Qwen command, follow the link to Qwen chat in your browser, and confirm/create an account.
  4. Configure Qwen CLI UI settings (for example, change theme and CLI language via the settings command).
  5. Create a project:
    • Use Qwen CLI to create an empty Next.js project (for example: “create an empty NextJS project”).
    • cd into the project folder and initialize the project so the agent recognizes the repo.
  6. Create .qwen/settings.json (a dot folder plus settings.json) to store local Qwen config.

MCP installation & connection

  • Read Qwen docs (the demo used Russian docs) for MCP integration templates.
  • MCP template pattern: an npx command is typically used to register MCPs (e.g., npx <mcp-install> with arguments). Multiple MCPs can be comma-separated in the config.
  • Example MCP in the demo: a “visual enhancer” MCP that provides React/Next components (author referred to it as “shcn” / “shn” as an example).
  • After editing settings, exit and restart Qwen CLI so it connects to MCPs.
  • Run qwen mcp list (or equivalent) to confirm MCPs are connected and to view available tools/prompts.

Skills creation & installation

  • Skills live under a /skills directory; each skill is a skill.md file containing description, instructions, and examples.
  • You can download existing skills (the presenter used mcpmarket.com as an example marketplace) and place them into your project’s /skills folder (e.g., skills/react/skill.md).
  • Reload or reinitialize Qwen for skills to become available to the agent.

Creating the project specification and roadmap

  • Use any modern LLM/chat (Qwen, GPT, Claude) to describe your project: features, screens, tech choices, and examples.
  • Ask the model to produce:
    • project.md — project specification in Markdown describing architecture, tech stack, tables, endpoints, pages, styles.
    • steps.md — a step-by-step development roadmap with iterative tasks.
  • Save these Markdown files in the project folder and attach/reference them when running the Qwen agent.

Agent execution workflow

  • Tell Qwen CLI to create the project, reference project.md and steps.md, and include configured MCPs/Skills.
  • The agent:
    • Reads the specs and roadmap.
    • Selects required MCPs/Skills.
    • Runs tasks iteratively (double-checks, runs installs, modifies files).
  • Qwen can automatically search for and suggest MCPs/Skills relevant to the project. The presenter recommended searching for MCPs/Skills in English and suggested using GPT/Claude for better selection.

Prompt engineering workflow

  • Upload a prompt template that asks structured questions (the demo’s example asked five key questions about scope and functionality).
  • The agent asks you those questions, then generates a high-quality prompt to drive the coding process.
  • This meta-prompt method customizes the generated prompt to your needs (UI visuals, frameworks, icons, styles, etc.) and improves results.

Example outcome (demo)

  • The presenter built a pizzeria Next.js app using this workflow.
  • Started the dev server with npm run dev and previewed the site on localhost.
  • Demo features shown: sliders, product images, add-to-cart, and cart flows — the site worked according to the spec.

Recommendations, caveats, and tips

  • Always use the latest Node.js.
  • Use an editor like VS Code to view and edit generated project files.
  • Qwen free tier is useful but limited; better MCP/skill selection may be achieved with more powerful LLMs (Claude, GPT).
  • Search for MCPs/Skills in English for better results — many MCP lists and skill marketplaces exist.
  • Use structured Markdown specs and step roadmaps — the agent executes more reliably when given formatted instructions.
  • Be aware that some names/terms in video transcripts can be OCR/mis-transcriptions; assume references to Qwen CLI, MCP examples, and skill marketplaces.

Note: transcript contains some auto-generated inaccuracies (e.g., “shcn”, “QVN”, “Quen”). Treat these as likely misspellings or OCR errors.

Quick checklist to replicate

  1. Install Node.js -> install Qwen CLI -> authenticate.
  2. Configure CLI UI (language/theme) -> create project via Qwen (Next.js).
  3. cd into project -> initialize Qwen in the project.
  4. Create .qwen/settings.json -> add MCP configuration (use the npx template).
  5. Restart Qwen CLI -> qwen mcp list (verify connections).
  6. Add /skills/<skill>/skill.md for needed capabilities.
  7. Produce project.md and steps.md (via chat/LLM) and place them into the project.
  8. Run Qwen “create” (or appropriate command) referencing the docs/specs -> let the agent implement.
  9. npm run dev -> test the app on localhost.

Primary speaker and sources

  • Speaker: Kostya (presenter).
  • Tools / sources referenced: Qwen CLI (Qwen 3.5+), Qwen chat web auth, Qwen documentation (Russian), MCP servers and marketplaces (example: mcpmarket.com), Node.js, Next.js, Visual Studio Code, Playwright (example browser-control MCP), GPT/Claude (for MCP/skill selection).

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