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官方说明3 个来源MCP 服务3 天前
kapilduraphe/mcp-watch

kapilduraphe/mcp-watch

Security scanner for MCP servers
在 GitHub 查看 ↗直链 · 无中转页
来源明细
收录自 abordage/awesome-mcp 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-14 · 最近见到 2026-10-16 · 共见到 4 次 · 被 3 个来源列出
评分构成
综合分 303 · 3 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
我们收录于 2026-10-14;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

MCP Watch 🔍

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

A comprehensive security scanner for Model Context Protocol (MCP) servers that detects vulnerabilities and security issues in your MCP implementations.
Features
- **🔑 Credential Detection** - Finds hardcoded API keys, tokens, and insecure credential storage
- **🧪 Tool Poisoning** - Detects hidden malicious instructions in tool descriptions
- **🎯 Parameter Injection** - Identifies magic parameters that extract sensitive AI context
- **💉 Prompt Injection** - Scans for prompt manipulation and injection attacks
- **🔄 Tool Mutation** - Detects dynamic tool changes and rug-pull risks
- **💬 Conversation Exfiltration** - Finds triggers that steal conversation history
- **🎨 ANSI Injection** - Detects steganographic attacks using escape sequences
- **📋 Protocol Violations** - Identifies MCP protocol security violations
- **🛡️ Input Validation** - Finds command injection, SSRF, and path traversal issues
- **🎭 Server Spoofing** - Detects servers impersonating popular services
- **🌊 Toxic Flows** - Identifies dangerous data flow patterns
- **🔐 Permission Issues** - Finds excessive permissions and access control problems
Quick Start 🚀
Option 1: NPM Package (Recommended)
Option 2: From GitHub Source
Option 3: Docker (No Installation)
Installation
Global Installation
Local Installation
From Source
Docker Installation 🐳
Quick Start with Docker
Docker Compose (Recommended for Production)
Docker Features
- **🔒 Security**: Non-root user, minimal attack surface
- **📦 Optimized**: Multi-stage builds, Alpine Linux base
- **🚀 Production**: Ready for deployment and CI/CD
- **🧹 Simplified**: Single optimized Dockerfile for all use cases
Usage
Command Line
Scan GitHub Repositories
Scan Local Projects
Installation Method Usage
From NPM Package
From GitHub Source
Docker Usage 🐳
Options
- --format - Output format: console (default) or json
- --severity - Minimum severity: low, medium, high, critical
- --category - Filter by vulnerability category
Categories
- credential-leak - Hardcoded credentials and insecure storage
- tool-poisoning - Malicious tool descriptions
- data-exfiltration - Data theft and parameter injection
- prompt-injection - Prompt manipulation attacks
- tool-mutation - Dynamic tool changes
- steganographic-attack - Hidden content in escape sequences
- protocol-violation - MCP protocol security issues
- input-validation - Command injection, SSRF, path traversal
- server-spoofing - Server impersonation
- toxic-flow - Dangerous data flows
- access-control - Permission and access issues
Example Output
Development
Project Structure
Development Scripts
Development Workflow 🚀
Local Development (Recommended)
Docker Development 🐳
Adding New Scanners
1. Create a new scanner in scanner/scanners/
2. Extend AbstractScanner
3. Implement the scan() method
4. Add to MCPScanner.ts
Example:
Security Research
This tool is based on security research from leading organizations in AI and cybersecurity, identifying novel attack vectors specific to MCP environments including:
- **Parameter injection attacks** that extract sensitive AI context
- **Tool poisoning** with hidden malicious instructions
- **Conversation exfiltration** using trigger phrases
- **Steganographic attacks** via ANSI escape sequences
- **Toxic agent flows** across repository boundaries
来源
awesome · https://github.com/kapilduraphe/mcp-watch
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