Agent Proxy

An AI supervisor layer that orchestrates coding agents (Claude Code, Cursor, etc.) to complete complex development tasks autonomously.

How It Works

Agent Proxy sits between human developers and AI coding agents, acting as an intelligent supervisor that:

1. Maintains Context - Stores project context, coding standards, and session history
2. Supervises & Assigns - Breaks down tasks and delegates to coding agents
3. Unblocks - Auto-responds to agent clarification requests
4. Verifies - Reviews agent output for correctness and quality
5. Aligns & Refocuses - Keeps agents on track toward the goal

Architecture

The proxy maintains three types of context:

• Project Context: Company mission, OKRs, competitive analysis, mockups
• Guidance & Practice: Coding standards, QA checklists, team preferences
• Sprint Session Context: Current tasks and their status

Execution Flow

1. Human provides one-time project context setup
2. Human assigns high-level tasks
3. Proxy Agent thinks, plans, and invokes the Coding Agent
4. Coding Agent executes steps, may ask for clarification
5. Proxy Agent auto-replies or redirects as needed
6. Proxy verifies results and updates task status
7. Final delivery presented to human

Setup

pip install fastapi uvicorn pydantic
echo "GEMINI_API_KEY=your_key" > .env

Mode 1: CLI

python cli.py "Create hello.py"
python cli.py -d ./myproject "Fix bug"
python cli.py --add-screenshot design.png "Match this UI"

# Add alias to ~/.zshrc or ~/.bashrc
alias pa='python /Users/ethw/Desktop/GIT-Aertoria/agentproxy/cli.py'

# Set working directory with task (saves to ~/.pa_config for future tasks)
pa --set-workdir ./myproject "Fix bug"
pa --show-workdir  # View current default

# Example with screenshot
pa --add-screenshot design.png "Build a web app matching this UI"

Mode 2: Server

python server.py --port 8080

# Start task
curl -N -X POST http://localhost:8080/task \
  -H "Content-Type: application/json" \
  -d '{"task": "Create hello.py", "working_dir": "./sandbox"}'

# With screenshot
curl -N -X POST http://localhost:8080/task \
  -H "Content-Type: application/json" \
  -d '{"task": "Match this UI", "screenshots": [{"path": "/path/to/design.png"}]}'

# Other endpoints
curl http://localhost:8080/health
curl http://localhost:8080/sessions

Requirements

• Python 3.9+
• Claude CLI (claude command)
• Gemini API key