Proxilion安全网关 是 AI Skill Hub 本期精选MCP工具之一。综合评分 7.5 分,整体质量较高。我们推荐使用将其纳入你的 AI 工具库,帮助提升工作效率。
Proxilion安全网关 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
Proxilion安全网关 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/clay-good/proxilion-mcp
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"proxilion----": {
"command": "npx",
"args": ["-y", "proxilion-mcp"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 Proxilion安全网关 执行以下任务... Claude: [自动调用 Proxilion安全网关 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"proxilion____": {
"command": "npx",
"args": ["-y", "proxilion-mcp"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
Real-time threat detection for AI coding assistants. Analyzes MCP tool calls to detect insider threats, compromised accounts, and rogue AI agents before they can weaponize Claude Code, GitHub Copilot, Cursor, or Windsurf.
---
ENABLE_SEMANTIC_ANALYSIS=false ANTHROPIC_API_KEY=sk-ant-xxx ```
cargo bench -p threat-engine
k6 run loadtest/baseline.js
```bash git clone https://github.com/clay-good/proxilion cd proxilion
```bash cargo build --release
cd packages/mcp-proxilion-middleware && npm install && npm run build npm link # or copy to your project
cd packages/proxilion-mcp-python && pip install -e . ```
Proxilion does NOT authenticate users. Deploy architecture:
Client (with auth token)
|
v
API Gateway / Reverse Proxy (OAuth, API key validation)
|
v
Proxilion Gateway (threat analysis)
|
v
MCP Server (tool execution)
cd tools && cargo build --release ./target/release/cost-calculator --requests 100000
cp proxilion-policy.example.toml proxilion-policy.toml
Note: Client libraries are included in this repository but not yet published to npm/PyPI. Install from local source:
```bash
./demo.sh
```bash
LISTEN_ADDR=0.0.0.0:8787 ALERT_THRESHOLD=50 BLOCK_THRESHOLD=70 TERMINATE_THRESHOLD=90
POLICY_FILE=./proxilion-policy.toml
| Crate | Purpose |
|---|---|
gateway | HTTP API server (Axum), request routing, operational modes |
threat-engine | 22 pattern-based analyzers + 2 session-aware analyzers |
session-state | Redis/In-Memory/PostgreSQL session storage |
mcp-protocol | MCP JSON-RPC 2.0 parsing |
Pattern-Based (22): - Enumeration (nmap, masscan, port scanning) - Credential Access (.env, SSH keys, AWS credentials, /etc/shadow) - Exfiltration (curl to external IPs, pastebin uploads, netcat) - AI Velocity (automated execution patterns) - Prompt Engineering (jailbreak attempts) - Social Engineering (authority claims, roleplay manipulation) - Callback Validation (C2 detection, SSRF) - MCP Orchestration (malicious MCP chaining) - File Access (sensitive file patterns) - Task Fragmentation (command chaining, obfuscation) - Data Volume (bulk transfers, database dumps) - Privilege Escalation (sudo abuse, SUID) - Lateral Movement (SSH pivoting, internal network) - Hacking Tools (metasploit, hashcat, mimikatz) - Hallucination (AI fabrication detection) - Persistence (cron jobs, systemd, backdoors) - Defense Evasion (log clearing, firewall bypass) - Command and Control (reverse shells, Cobalt Strike) - Collection (data staging, screenshots) - Impact (destructive operations like rm -rf) - Tool Call (SQL injection, command chaining) - Legitimacy (context-aware false positive reduction)
Session-Aware (2): - Request Rate (burst detection, machine-like velocity) - Session Progression (kill chain tracking: Recon -> Credentials -> Exfiltration)
Additional Analyzers (6, require explicit configuration): - AI Autonomy (autonomous agent detection) - Conversation Analysis (social engineering via conversation context) - Conversation Context (multi-turn tracking) - Multi-Target Orchestration (parallel target operations) - Multi-User Correlation (coordinated attacks across users) - Semantic Analysis (Claude API-based intent analysis, optional feature flag)
---
./target/release/cost-calculator --compare
Example output: PROXILION SEMANTIC ANALYSIS COST ESTIMATE ═══════════════════════════════════════════════════════════════ Monthly requests: 100,000 Ambiguous rate: 30.0% Result cache hit rate: 40.0%
TOTAL MONTHLY COST: $64.06 Cost per request: $0.000641 ```
---
Proxilion MCP 安全网关是实时威胁检测工具,用于分析 MCP 工具调用以检测内部威胁、被破坏的账户和恶意 AI 代理,防止它们在使用 Claude 代码、GitHub Copilot、Cursor 或 Windsurf 之前被武器化。
Proxilion MCP 安全网关的功能包括:
环境依赖与系统要求:
API/接口说明:
工作流 / 模块说明:
高质量的开源MCP工具,值得关注
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
经综合评估,Proxilion安全网关 在MCP工具赛道中表现稳健,质量良好。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | proxilion-mcp |
| 原始描述 | 开源MCP工具:Proxilion MCP Security Gateway is a self-hosted, Docker-ready security gateway t。⭐6 · Rust |
| Topics | mcpcybersecuritydockerrust |
| GitHub | https://github.com/clay-good/proxilion-mcp |
| License | MIT |
| 语言 | Rust |
收录时间:2026-06-06 · 更新时间:2026-06-06 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端