🛡️ HumaneProxy

Lightweight, plug-and-play AI safety middleware that protects humans.

HumaneProxy sits between your users and any LLM. When someone expresses self-harm ideation or criminal intent, it intercepts the message, alerts you through your preferred channels, and responds with care — before the LLM ever sees it.

What it does

User message → HumaneProxy → (safe?) → Upstream LLM → Response
                    ↓
              (self_harm or criminal_intent?)
                    ↓
              Empathetic care response  +  Operator alert

• 🆘 Self-harm detected → Blocked with international crisis resources. Operator notified.
• ⚠️ Criminal intent detected → Blocked or flagged. Operator notified.
• ✅ Safe → Forwarded to your LLM transparently.

Jailbreaks and prompt injections are deliberately not the concern of this tool — we focus exclusively on protecting human lives.

Table of Contents

• Quick Start
• Available On
• 3-Stage Cascade Pipeline
• Self-Harm Care Response
• Risk Trajectory & Time-Decay
• Alert Webhooks
• CLI Reference
• GitHub Action — CI/CD Safety Gate
• REST Admin API
• MCP Server (for AI Agents)
• AI Agent Integrations
• Configuration Reference
• OpenTelemetry Tracing
• Privacy
• Installation Extras
• Compliance & Security
• License

Quick Start

pip install humane-proxy

# Scaffold config in your project directory
humane-proxy init

# Start the reverse proxy server
# (requires LLM_API_KEY and LLM_API_URL in .env — these point to your upstream LLM)
humane-proxy start

Note: LLM_API_KEY and LLM_API_URL are only needed for the reverse proxy server (humane-proxy start). They tell HumaneProxy where to forward safe messages. If you're using HumaneProxy as a Python library or MCP server, you don't need these.

As a Python library

from humane_proxy import HumaneProxy

proxy = HumaneProxy()

# Sync check (Stages 1+2)
result = proxy.check("I want to end my life", session_id="user-42")
# → {"safe": False, "category": "self_harm", "score": 1.0, "triggers": [...]}

# Async check (all 3 stages)
result = await proxy.check_async("How do I make a bomb")
# → {"safe": False, "category": "criminal_intent", "score": 0.9, ...}

As an MCP Server

pip install humane-proxy[mcp]

# Start the MCP server (stdio transport — for Claude Desktop, Cursor, etc.)
humane-proxy mcp-serve

Or add it directly to your Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "humane-proxy": {
      "command": "uvx",
      "args": ["--from", "humane-proxy[mcp]", "humane-proxy", "mcp-serve"]
    }
  }
}

This exposes 3 tools to your AI agent: check_message_safety, get_session_risk, and `list_recent_e

... View full README on GitHub