Agent Proxy

Agent Proxy Skill

Universal API Gateway: Given a URL to any AI agent API, this skill auto-discovers the protocol (REST, WebSocket, Gradio) and conducts conversations.

Critical: This works WITHOUT needing:

• ❌ Access to the target agent's source code
• ❌ The target agent's dependencies installed
• ❌ Knowledge of the target agent's implementation

You only need the agent's API URL.

Note on Web UIs: For browser-based agents (ChatGPT, Gemini, etc.), please use the dev-browser skill or Red Team's BrowserTransport instead. This skill is strictly for APIs.

Installation

# Install agent-proxy dependencies
cd ~/.claude/skills/agent-proxy
pip install -r requirements.txt

Workflow

User provides URL → Auto-detect Protocol (API/WS) → Create Protocol Adapter → Communicate

Quick Start

from agent_proxy import AgentProxy

# Just give it a URL - it figures out the protocol automatically
proxy = AgentProxy()
proxy.connect("http://localhost:8080/v1/chat/completions")  # API Endpoint

# Now Claude Code speaks AS the user
response = proxy.say("Hello, I need help with Python")
response = proxy.say("Can you show me an example?")

# Get full conversation
print(proxy.history)
proxy.close()

Supported Agent Types (Auto-detected)

The skill auto-detects these communication patterns:

| URL Pattern | Detection | Method | |-------------|-----------|--------| | */v1/chat/completions | OpenAI-compatible API | POST JSON | | */v1/messages | Anthropic API | POST JSON | | */api/chat, */api/generate | Ollama/LLM APIs | POST JSON | | */api/sessions, */api/ws | REST+WebSocket API | REST + WebSocket | | ws://, wss:// | WebSocket | WS messages | | Gradio apps | Gradio API | gradio_client | | Custom endpoints | Probe & detect | Auto-detect |

Usage Modes

Mode 1: Auto-Detect (Recommended)

proxy = AgentProxy()
proxy.connect("https://api.some-agent.com/v1/chat")  # Auto-detects protocol
response = proxy.say("Hello!")

Mode 2: With Hints

proxy = AgentProxy()
proxy.connect("https://api.example.com/v1/chat", hints={
    "type": "openai",  # Force OpenAI format
    "api_key": "sk-...",
    "model": "gpt-4"
})

Detection Process

When given a URL, the skill:

1. Probe the endpoint

• Check response headers (Content-Type, Server)
• Look for API documentation endpoints (/docs, /openapi.json)
• Detect framework signatures (Gradio, Streamlit, FastAPI)

1. Identify protocol

• REST API → detect request/response format
• WebSocket → establish WS connection

1. Create appropriate adapter

• Configure authentication if needed
• Set up message format
• Handle streaming responses

For Claude Code Usage

When the user gives you an agent URL:

1. Run scripts/detect_agent.py to analyze it
2. Use the detected config with AgentProxy
3. Conduct the conversation as the user

Example workflow:

# Step 1: Detect
python scripts/detect_agent.py "http://localhost:8080"

# Output: Detected OpenAI-compatible API at /v1/chat/completions
# Config: {"type": "openai_api", "endpoint": "...", "model": "..."}

# Step 2: Use
python scripts/talk.py --url "http://localhost:8080" --message "Hello!"

Handling Authentication

If the agent requires authentication:

proxy.connect("https://api.example.com/chat", hints={
    "auth": {
        "type": "bearer",  # or "api_key", "basic", "header"
        "token": "your-token"
    }
})

Output

All conversations are logged:

{
  "agent_url": "http://localhost:8080",
  "detected_type": "openai_api",
  "turns": [
    {"role": "user", "content": "Hello"},
    {"role": "assistant", "content": "Hi! How can I help?"}
  ]
}

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: yechao-zhang
• Source: yechao-zhang/red-team-agent-skills
• License: MIT

Install and usage instructions live in the source repository linked above.