AI-powered CLI development assistant
Project description
Cognix
Autonomous code generation powered by flow engineering.
Installation
pipx install cognix
or pip install cognix. Requires Python 3.9+.
For Windows binary installation, see INSTALL.md.
Quick Start
# Setup API key
echo "ANTHROPIC_API_KEY=your_key" > .env
# Run
cognix
# Generate code from a spec file (sample included)
cognix> /make @sample_spec_tetris.md
# Or describe what you want
cognix> /make "landing page with HTML and CSS"
A sample spec file sample_spec_tetris.md is included in the repository. Use it as a reference for writing your own specs.
For available commands, type /help in the CLI.
Linting with ruff is included by default. Additional linters (flake8, pylint) are auto-detected if installed.
Windows binary
Download cognix.exe from Releases. No Python installation required.
Model Configuration
Anthropic Claude (Default)
ANTHROPIC_API_KEY=sk-ant-your_key
# Supports: Sonnet 4.5 (default), Opus 4.5
OpenAI
OPENAI_API_KEY=sk-your_key
# Supports: GPT-5.2, GPT-5.2 Codex
OpenRouter
OPENAI_API_KEY=sk-or-v1-your_key
OPENAI_BASE_URL=https://openrouter.ai/api/v1
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/
├── config.json # Settings
├── memory.json # Conversation & project memory
├── repository_data.json # Repository analysis data
├── ui-knowledge.json # UI knowledge base
├── sessions/ # Saved sessions
├── knowledge/ # App pattern definitions
├── rules/ # File reference rules
├── backups/ # Automatic backups
└── impact_analysis/ # Impact analysis results
No telemetry. API calls only to configured LLM provider.
Links
GitHub: github.com/cognix-dev/cognix Issues: GitHub Issues Discussions: GitHub Discussions
License
Apache-2.0 License - see LICENSE file
Project details
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