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AI-powered CLI development assistant

Project description

Cognix

Autonomous code generation powered by flow engineering.

Version License Python


Quick Start

1. Install and run

pipx install cognix
cognix

2. First-time setup

When you run Cognix for the first time, an interactive wizard will help you set up your API key:

  • Choose your AI provider (Anthropic, OpenAI, or OpenRouter)
  • Enter your API key
  • The wizard creates a ~/.cognix/.env file automatically

3. Generate code

Try the included sample first (use @ to specify a file):

cognix> /make @sample_spec_tetris.md

Or describe what you want to build:

cognix> /make "landing page with HTML and CSS"

A sample specification file sample_spec_tetris.md is included in the repository. Use it as a reference for writing your own specifications.

4. Available commands

Type /help in the CLI to see all available commands.


API Key Setup

Automatic setup (recommended)

Just run cognix and follow the interactive wizard.

Manual setup

Edit the ~/.cognix/.env file (Windows: C:\Users\<username>\.cognix\.env):

Anthropic Claude (default):

ANTHROPIC_API_KEY=sk-ant-your_key_here

Get your key at: https://console.anthropic.com/

Supported models: Sonnet 4.5 (default), Opus 4.6, Opus 4.5

OpenAI:

OPENAI_API_KEY=sk-your_key_here

Get your key at: https://platform.openai.com/api-keys

Supported models: GPT-5.2, GPT-5.2 Codex

OpenRouter:

OPENAI_API_KEY=sk-or-v1-your_key_here
OPENAI_BASE_URL=https://openrouter.ai/api/v1

Get your key at: https://openrouter.ai/keys

Switch models

cognix> /model

MCP Server Integration

Use Cognix from Claude Desktop, Cursor, VSCode, or any MCP-compatible tool.

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "cognix": {
      "command": "cognix-mcp"
    }
  }
}

Data Storage

Cognix stores data in ~/.cognix/:

~/.cognix/
├── .env                            # API keys & credentials
├── config.json                     # Your settings
├── memory.json                     # Conversation & project memory
├── repository_data.json            # Repository analysis cache
├── ui-knowledge.json               # UI component knowledge
├── app_patterns.json               # App pattern definitions
├── default_file_reference_rules.md # File reference rules
├── sessions/                       # Saved work sessions
├── backups/                        # Automatic backups
├── logs/                           # Debug logs
├── temp/                           # Temporary files
└── impact_analysis/                # Code impact analysis results

Privacy: No telemetry. API calls only go to your configured LLM provider.


System Requirements

  • OS: Windows 10+, macOS 10.15+, or Linux
  • Python: 3.9 or higher
  • Internet: Required for LLM API access

Links


License

Apache-2.0 License - see LICENSE file for details

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