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picadolabs/build-with-ai

Developer tools
5 stars 24 forks Quality 73 Trend 33NOASSERTION

Step-by-step guided AI development workflows, architectural decision tracking, and native MCP server for Cursor, Claude, and Copilot.

Overview

Prompting an AI model to "build an entire app" typically breaks down in three ways: 1. : Monolithic prompts produce hallucinated schemas and unmaintainable code dumps. 2. : In long conversations, AI forgets early database designs, auth models, and naming standards. 3. : Models jump to frontend polish before data models, contracts, and error handling exist. build-with-ai solves this by breaking application development into structured, sequential engineering phases. It records decisions in a local context.json file and automatically injects them into downstream prompts ({{decisions.key}}). - : Runs 100% locally in your terminal. Works out of the box with web UIs (ChatGPT, Claude), IDEs (Cursor, Windsurf), or local LLMs (Ollama). - : Generates tailored prompts for any AI model without vendor lock-in. - : State is maintained exclusively inside .buildwithai/ and never alters your application code unexpectedly.

README

build-with-ai


Why build-with-ai?

Prompting an AI model to “build an entire app” typically breaks down in three ways:

  1. The Blank Canvas Problem: Monolithic prompts produce hallucinated schemas and unmaintainable code dumps.
  2. Context Drift: In long conversations, AI forgets early database designs, auth models, and naming standards.
  3. Skipped Foundations: Models jump to frontend polish before data models, contracts, and error handling exist.

build-with-ai solves this by breaking application development into structured, sequential engineering phases. It records decisions in a local context.json file and automatically injects them into downstream prompts ({{decisions.key}}).

Key Principles

  • Zero API Keys & Zero Cost: Runs 100% locally in your terminal. Works out of the box with web UIs (ChatGPT, Claude), IDEs (Cursor, Windsurf), or local LLMs (Ollama).
  • Universal Compatibility: Generates tailored prompts for any AI model without vendor lock-in.
  • Non-Destructive: State is maintained exclusively inside .buildwithai/ and never alters your application code unexpectedly.
  • AI Editor Ready: Ships with a native Model Context Protocol (MCP) server and automatic editor rules synchronization (.cursorrules, CLAUDE.md, etc.).

Quickstart

Run directly without prior installation:

npx build-with-ai

Or install globally:

npm install -g build-with-ai

Initialize your workspace:

npx build-with-ai init

The 4-Step Workflow

graph LR
    A["1. init"] --> B["2. next"]
    B --> C["3. AI Implementation"]
    C --> D["4. done"]
    D --> B
    D --> E["5. export"]

1. Initialize (init)

Select a technology template, your experience level, and a project summary:

npx build-with-ai init

2. Generate Prompt (next)

Formats the active phase requirements, identifies target files, and copies the context-injected prompt to your clipboard:

npx build-with-ai next

3. Record Decisions (done)

Paste the prompt into your AI tool, review the generated code, and record architectural decisions:

npx build-with-ai done

You can also parse decisions directly from the clipboard:

npx build-with-ai done --from-clipboard

4. Export & Sync Rules (export)

Export clean Markdown documentation and sync your project decisions across editor rule files:

npx build-with-ai export
npx build-with-ai export --rules

Available Templates

build-with-ai ships with 11 production-ready workflow templates:

Template ID Name Steps Core Stack
web-app Full-Stack Web Application 23 Next.js / React, Tailwind CSS, Prisma, PostgreSQL
saas-mvp Modern SaaS MVP 15 Next.js App Router, Supabase, Stripe, Resend
rest-api Backend REST API Service 10 Node.js, Fastify / Express, PostgreSQL, Zod
fastapi-backend Python FastAPI Microservices 12 Python 3.11+, FastAPI, Pydantic v2, SQLAlchemy 2.0, Alembic
mobile-app Cross-Platform Mobile App 15 React Native, Expo Router, NativeWind, EAS Build
flutter-app Flutter Mobile Application 16 Flutter 3.x, Dart, Riverpod / BLoC, Clean Architecture
electron-app Electron Desktop Application 12 Electron, Vite, React, IPC Handlers, electron-builder
chrome-extension Chrome Browser Extension 12 Manifest V3, Vite, React, Shadow DOM
ai-agent AI Agent & RAG Pipeline 14 LangChain / LlamaIndex, Vector DB, FastAPI / Express
ai-orchestration Multi-Agent Orchestration 14 LangGraph / CrewAI, AutoGen, Vector DB, Telemetry
discord-bot Discord Bot Workflow 12 Node.js, discord.js v14, Slash Commands, SQLite / PostgreSQL

Custom and Remote Templates

Load team-specific or custom templates from a local file or HTTPS URL:

# Local JSON template
npx build-with-ai init --template ./custom-template.json

# Remote HTTPS template
npx build-with-ai init --template https://raw.githubusercontent.com/org/repo/main/template.json

# Discover community templates
npx build-with-ai search saas

Custom templates are persisted to .buildwithai/template.json and work fully offline for all subsequent commands.


CLI Reference

Core Workflow

Command Description
npx build-with-ai Interactive launcher. Shows progress or initiates setup wizard.
npx build-with-ai init Start interactive setup (template, experience, overview).
npx build-with-ai next Generate and copy the current step prompt to the clipboard.
npx build-with-ai next --run BYOK autonomous mode: send prompt directly to AI provider.
npx build-with-ai done Record step decisions, archive step logs, and advance to next step.
npx build-with-ai undo Roll back most recent step, restore context snapshot, and prune history.
npx build-with-ai back Step back to previous step without removing recorded context.
npx build-with-ai jump [step] Navigate directly to a specific step number.

Context & Configuration

Command Description
npx build-with-ai status Display progress bar, completed steps, and active decisions.
npx build-with-ai context [key] Inspect recorded decisions or retrieve a specific dot-notation path.
npx build-with-ai set Update a decision in context.json directly from the CLI.
npx build-with-ai config Interactive key-picker to browse and edit decisions.
npx build-with-ai history [step] Inspect archived AI responses and step logs.
npx build-with-ai resume Summary dashboard displaying active state and recommended next action.

Documentation & Editor Rules

Command Description
npx build-with-ai export Generate README.md, BUILD_LOG.md, and .buildwithai/CONTEXT.md.
npx build-with-ai export --rules Sync decisions to .cursorrules, CLAUDE.md, .windsurfrules, and Copilot.
npx build-with-ai export --force Overwrite existing README.md without confirmation.
npx build-with-ai reset Clean .buildwithai/ state while preserving project source code.
npx build-with-ai mcp Launch Model Context Protocol (MCP) stdio server.

Advanced Capabilities

BYOK Autonomous Mode

Bring Your Own Key or use local Ollama to bypass copy-pasting. The CLI executes the step prompt, writes returned code files into your workspace, updates context.json, and advances the phase:

export OPENAI_API_KEY=sk-...
npx build-with-ai next --run

# Preview git-style diffs before files are written
npx build-with-ai next --run --review

# Use a local model with Ollama (no API key required)
npx build-with-ai next --run --provider ollama

Supported providers: openai, anthropic, gemini, deepseek, groq, together, ollama.

Model Context Protocol (MCP)

Start a native stdio MCP server to let AI coding tools drive the workflow:

npx build-with-ai mcp

Add to your editor configuration (.cursor/mcp.json or claude_desktop_config.json):

{
  "mcpServers": {
    "build-with-ai": {
      "command": "npx",
      "args": ["build-with-ai", "mcp"],
      "cwd": "/path/to/your/project"
    }
  }
}

Exposed tools: get_workflow_status, get_active_prompt, complete_step, and get_context. Steps completed via MCP automatically create safe rollback snapshots.

Editor Rules Synchronization

Keep your AI coding assistant anchored to the project’s architectural decisions:

npx build-with-ai export --rules

Updates:

  • .cursorrules and .cursor/rules/project-decisions.mdc
  • .windsurfrules
  • CLAUDE.md
  • .github/copilot-instructions.md

All user instructions outside the managed `` block are preserved.

Optionally, configure exported decisions in .buildwithai/rules.config.json:

{
  "includeKeys": ["decisions.database", "decisions.auth"],
  "excludeKeys": ["decisions.scratchNotes"]
}

Both keys are optional; includeKeys selects decisions, excludeKeys removes them, and exclusions take precedence. Without this file, all decisions are exported.

Branch-Scoped Storage

To isolate state across git branches, enable branch scoping:

export BUILD_WITH_AI_BRANCH_SCOPED=1

State is isolated under .buildwithai/branches//, ensuring feature branches do not collide.


Storage Architecture

All state is self-contained inside your project’s .buildwithai/ directory:

my-project/
├── .buildwithai/
│   ├── state.json        # Progress tracking and current step pointer
│   ├── context.json      # Structured architectural decisions (single source of truth)
│   ├── template.json     # Persisted template (for offline execution)
│   ├── snapshots/        # Step snapshots for non-destructive undo/rollback
│   ├── CONTEXT.md        # Formatted markdown view of decisions
│   └── history/          # Historical step responses (step-01.md, step-02.md, ...)
├── src/                  # User application code (never touched by CLI)
├── README.md             # Generated on export
└── BUILD_LOG.md          # Generated on export

Contributing

Contributions are welcome. Please read CONTRIBUTING.md for details on development setup, template specifications, and pull request guidelines.

Please review our Code of Conduct.


Security

To report security vulnerabilities, consult our Security Policy or contact [email protected].


Maintainer


License

Licensed under the Apache License 2.0.

Copyright © 2026 PicadoLabs.

View the full README on GitHub

Install

npx build-with-ai mcp
New to MCP? Start with the mcpskill.org guide →

Configuration

{ "mcpServers": { "build-with-ai": { "command": "npx", "args": ["build-with-ai", "mcp"], "cwd": "/path/to/your/project" } } }