superego-mcp

superego-mcp

Superego MCP is an intelligent tool-call review system for AI agents that provides configurable security rules and automated guardrails.

Category
访问服务器

README

Superego MCP

Python Version License Code Style Type Checked

Intelligent tool-call review system for AI agents

Overview

Superego MCP Server provides a configurable review system to AI agents to reduce the amount of manual approvals needed as well as provide automated guardrails against dangerous operations. It analyzes incoming tool calls against a set of rules and if no rule is matched it defers to another agent for review or escalation to a human.

Features

  • Rule-based interception: Define flexible rules using YAML configuration with advanced pattern matching (regex, glob, JSONPath)
  • Multiple actions: Allow, block, or require approval (sampling) based on configurable policies
  • Claude Code Hooks Integration: Direct integration with Claude Code for real-time security evaluation
  • Multi-transport Support: STDIO, HTTP, and SSE transports for flexible deployment
  • Hot reload: Configuration changes are applied without restart
  • AI-powered evaluation: Optional AI inference for complex security decisions
  • Performance optimized: Request batching, caching, and connection pooling
  • Comprehensive monitoring: Built-in metrics, health checks, and performance dashboard
  • Structured logging: Comprehensive logging with structured output
  • MCP compatibility: Full Model Context Protocol support with FastMCP framework

Quick Start

Installation

# Install with uv (recommended)
uv pip install superego-mcp

# Or install from source
git clone https://github.com/toolprint/superego-mcp
cd superego-mcp
uv sync

Basic Usage

  1. Run security evaluation (for Claude Code hooks):

    echo '{"tool_name": "bash", "tool_input": {"command": "ls"}}' | superego advise
    
  2. Start the MCP server:

    # Default STDIO transport
    superego mcp
    
    # HTTP transport on custom port
    superego mcp -t http -p 9000
    
    # With custom config
    superego mcp -c ~/.toolprint/superego/config.yaml
    
  3. Run interactive demo:

    just demo-fastagent-simple
    

Claude Code Integration

Superego provides seamless integration with Claude Code through hooks:

Setup Claude Code Hooks

# Add hooks for specific tools (recommended)
superego hooks add --matcher "Bash|Write|Edit|MultiEdit"

# Add universal hook for all tools
superego hooks add --matcher "*"

# Use centralized server mode
superego hooks add --matcher "*" --url http://localhost:8000

For complete hook setup instructions and examples, see: Claude Code Hooks Setup Guide

Quick Hook Configuration

{
  "hooks": {
    "PreToolUse": [
      {
        "matcher": "*",
        "hooks": [
          {
            "type": "command",
            "command": "superego advise",
            "timeout": 5000
          }
        ]
      }
    ]
  }
}

Configuration

Server Configuration (config/server.yaml)

# Server settings
host: "localhost"
port: 8000
debug: false
log_level: "INFO"

# Rule engine settings
rules_file: "config/rules.yaml"
hot_reload: true

# Multi-transport configuration
transport:
  stdio:
    enabled: true
  http:
    enabled: true
    host: "0.0.0.0"
    port: 8000
  sse:
    enabled: true
    port: 8002

# AI inference configuration
inference:
  timeout_seconds: 30
  provider_preference:
    - "claude_cli"
    - "mcp_sampling"
  cli_providers:
    - name: "claude_cli"
      enabled: true
      type: "claude"
      command: "claude"
      model: "claude-sonnet-4-20250514"

Security Rules (config/rules.yaml)

rules:
  # Block dangerous commands
  - id: "block_destructive_commands"
    priority: 1
    conditions:
      tool_name:
        type: "regex"
        pattern: "^(rm|delete|remove|destroy).*"
    action: "deny"
    reason: "Destructive command pattern detected"
    
  # Protect system directories
  - id: "protect_system_files"
    priority: 2
    conditions:
      parameters:
        path:
          type: "glob"
          pattern: "/etc/**"
    action: "deny"
    reason: "System directory access denied"
    
  # Require approval for file operations
  - id: "sample_file_operations"
    priority: 10
    conditions:
      AND:
        - tool_name: ["edit", "write", "delete"]
        - parameters:
            path:
              type: "regex"
              pattern: "^(?!/tmp/).*$"
    action: "sample"
    reason: "File operation requires AI evaluation"
    sampling_guidance: "Evaluate if this file operation is safe"

Development

Setup

# Setup development environment
just dev

# Run tests
just test

# Run with coverage
just test-cov

# Lint and format
just lint
just format

# Type check
just typecheck

# Run all quality checks
just check

Project Structure

src/superego_mcp/
├── __init__.py              # Package initialization
├── cli.py                   # Unified CLI interface
├── cli_eval.py              # Evaluation mode implementation  
├── cli_hooks.py             # Claude Code hooks management
├── main.py                  # MCP server entry point
├── main_optimized.py        # Performance-optimized server
├── stdio_main.py            # STDIO transport handler
├── domain/                  # Business logic and models
│   ├── models.py            # Core domain models
│   ├── pattern_engine.py    # Pattern matching engine
│   ├── security_policy.py   # Security evaluation engine
│   ├── services.py          # Domain services
│   ├── repositories.py      # Domain repositories
│   ├── claude_code_models.py # Claude Code hook models
│   └── hook_integration.py  # Hook integration service
├── infrastructure/          # External services and adapters
│   ├── config.py            # Configuration management
│   ├── config_watcher.py    # Hot reload implementation
│   ├── ai_service.py        # AI inference service
│   ├── inference.py         # Extensible inference system
│   ├── circuit_breaker.py   # Circuit breaker pattern
│   ├── metrics.py           # Prometheus metrics
│   ├── performance.py       # Performance optimization
│   └── logging_config.py    # Structured logging setup
└── presentation/            # API and transport layers
    ├── mcp_server.py        # FastMCP server implementation
    ├── http_transport.py    # HTTP/WebSocket transport
    ├── sse_transport.py     # Server-sent events transport
    ├── handlers.py          # Request handlers
    ├── monitoring.py        # Monitoring dashboard
    └── server.py            # Transport server orchestration

Testing

# Run specific test file
just test-file tests/test_security_policy.py

# Run integration tests
uv run pytest tests/test_mcp_server_integration.py -v

# Run performance tests
just test-performance

# Run load tests
just load-test

Performance Optimization

# Run optimized server
just run-optimized

# Run performance demo
just demo-performance

# Benchmark rule evaluation
just benchmark-rules

API Documentation

CLI Commands

  • superego advise - One-off security evaluation for Claude Code hooks
  • superego mcp - Launch the FastMCP server
  • superego hooks - Manage Claude Code hook configurations

Tool Request Format

{
  "tool_name": "string",
  "tool_input": {
    "parameter1": "value1",
    "parameter2": "value2"
  },
  "session_id": "string",
  "transcript_path": "string",
  "cwd": "string",
  "hook_event_name": "PreToolUse"
}

Security Decision Response

{
  "decision": "allow|deny|sample",
  "confidence": 0.95,
  "reasoning": "Explanation of the decision",
  "risk_factors": ["risk1", "risk2"],
  "matched_rules": ["rule_id1", "rule_id2"]
}

Monitoring

Access the monitoring dashboard at http://localhost:9090/dashboard when running with metrics enabled.

Metrics available:

  • Request volume by tool type
  • Decision distribution (allow/deny/sample)
  • Processing times
  • AI inference latency
  • Error rates

Troubleshooting

Common Issues

  1. Import errors: Ensure proper Python path setup

    export PYTHONPATH=$PYTHONPATH:$(pwd)/src
    
  2. Hook timeouts: Check Superego service availability

    superego mcp --debug
    
  3. AI inference failures: Verify API keys are set

    export ANTHROPIC_API_KEY=your-key-here
    

Debug Mode

Enable debug logging:

superego mcp --debug

Logs Location

  • Server logs: stderr (structured JSON format)
  • Hook operations: /tmp/superego_hook.log
  • Metrics: http://localhost:9090/metrics

Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'feat: add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Development Guidelines

  • Follow conventional commits format
  • Ensure all tests pass (just check)
  • Add tests for new features
  • Update documentation as needed
  • Maintain type safety with mypy

License

MIT License - see LICENSE file for details

Container Deployment

Docker Quickstart

  1. Pull the latest image:
docker pull toolprint/superego-mcp:latest
  1. Run with Docker Compose:
# Start in development mode
docker-compose up -d

# Start in production mode
docker-compose -f docker-compose.prod.yml up -d

Container Management

Links

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选