Burp Suite for AI Agent
Two-way Burp Suite MCP bridge enabling AI agents to capture traffic, analyze endpoints, queue scans, and send findings back to Burp.
README
<p align="center"> <img src="https://readme-typing-svg.herokuapp.com?font=Fira+Code&weight=600&size=28&duration=3000&pause=500&color=FF6633¢er=true&vCenter=true&width=500&lines=Burp+Suite+for+AI+Agent;MCP+Bridge+%2B+Jython+Plugin" alt="Typing SVG" /> </p>
<p align="center"> <b>Two-way Burp Suite MCP bridge — AI agents capture traffic, analyze endpoints, queue scans, and send findings back to Burp.</b> </p>
<p align="center"> <img src="https://img.shields.io/badge/Node.js_18%2B-339933?style=flat&logo=nodedotjs&logoColor=white" /> <img src="https://img.shields.io/badge/Burp_Jython_2.7-FF6633?style=flat&logo=burpsuite&logoColor=white" /> <img src="https://img.shields.io/github/license/whoismemas/burpsuite-for-ai-agent" /> </p>
📁 Structure
burpsuite-for-ai-agent/
├── src/
│ └── index.js ← MCP server (HTTP bridge + 11 MCP tools)
├── plugin/
│ └── burpAI.py ← Jython 2.7 Burp plugin (context menu, auto-forward, outbound polling)
├── package.json ← Node.js manifest (dependencies: @modelcontextprotocol/sdk, zod)
├── .gitignore
└── README.md
Architecture
Burp Suite (Linux / Windows)
└─ plugin/burpAI.py (Jython plugin)
│ POST /ingest (127.0.0.1:9999)
│ GET /burp/outbound (poll every 2s)
▼
src/index.js ← MCP server (HTTP bridge + 11 MCP tools)
│
▼
AI Agent ←→ MCP tools
Linux: Burp + server + agent — all on one machine. Windows + WSL: Burp on Windows, server + agent in WSL over localhost.
Quick Install (one command)
bash install.sh
This runs npm install, prints Burp plugin instructions, and generates .mcp.json for AI agent auto-registration.
Quick Start
1. MCP server
node src/index.js
2. Load Burp plugin
- Burp Suite → Extensions → Installed → Add
- Extension type:
Python(requires Jython 2.7 standalone JAR) - File:
plugin/burpAI.py
3. Verify
In Burp's burpAI tab, click Check Status. Connected:
{ "ok": true, "requests": 0, "endpoints": 0 }
MCP Tools (16 tools)
| Tool | Description |
|---|---|
burp_status |
Bridge connection status + store statistics |
burp_requests |
List captured HTTP requests (filter by url/method) |
burp_request_detail |
Full request/response (headers, body) |
burp_endpoints |
Unique endpoints with parameter names, hit counts |
burp_tasks |
Scan/plan/scope tasks queued from Burp context menu |
burp_issues |
Security findings queued for Burp import |
burp_import_issue |
Submit a finding (title, url, severity, detail) |
burp_snapshot |
Latest session snapshot (cookies, storage) |
burp_send_to_burp |
Queue action: send_to_repeater, add_scan_issue, console_log |
burp_replay |
Modify captured request → send to Burp Repeater |
burp_outbound_status |
Pending outbound actions |
burp_scan_url |
Run nuclei scan against a single URL |
burp_scan_bulk |
Run nuclei scan against all captured endpoints |
burp_scan_results |
List/display nuclei scan results |
burp_scan_import_all |
Import nuclei findings as Burp issues |
burp_clear |
Clear all captured data |
Workflow
Capture → Analyze
Right-click a request in Burp (Proxy/Repeater) → burpAI: send request(s)
Agent:
burp_requests— list captured requestsburp_endpoints— enumerate endpointsburp_request_detail— full request/response
Queue scan → Execute
Right-click → burpAI: send + queue scan
Agent picks up via burp_tasks.
Finding → Burp Scanner
Agent calls burp_import_issue → Burp tab → Import Issues
Agent → Burp Repeater
Agent calls burp_send_to_burp with type send_to_repeater → Burp opens Repeater tab.
Agent-Driven Scanning
This is the core custom scanner flow: Burp captures → agent thinks → agent modifies → Burp executes.
Burp (Proxy → History)
│ right-click → burpAI: send request(s)
▼
MCP server ←── captures request
│
▼
Agent reads via burp_requests / burp_request_detail
│
│ Agent thinks: "endpoint /api/login takes username, try SQLi"
│
▼
Agent calls burp_replay({
request_id: "burp:burp-12345",
set_body: '{"username":"admin\\' OR 1=1--","password":"x"}'
})
│
▼
MCP server → Burp Repeater → Burp executes HTTP call
│
▼ (auto-forward enabled)
Response captured back → Agent reads & analyzes
│
▼
burp_import_issue → if vulnerable
Key tool: burp_replay takes a captured request ID, applies modifications (method, path, headers, body), and sends it to Burp Repeater. No need to manually craft raw bytes — the agent just specifies what to change.
Requirements:
- Enable Auto-send Repeater responses in Burp plugin settings
- This ensures the agent sees every Repeater response automatically
External Scanning (nuclei)
Optionally run nuclei scans directly from the bridge:
| Tool | Use case |
|---|---|
burp_scan_url |
Scan one URL with nuclei templates |
burp_scan_bulk |
Scan all captured endpoints at once |
burp_scan_results |
Review scan history |
burp_scan_import_all |
Import nuclei findings as Burp issues |
Nuclei must be installed on the same machine. Findings with High/Critical severity are auto-imported as Burp issues.
Auto-Forwarding
| Feature | Description |
|---|---|
| Auto-send Proxy responses | All Proxy traffic sent to MCP server |
| Auto-send Repeater responses | Repeater traffic automatically forwarded |
| Forward Burp Scanner issues | Scanner findings pushed to agent |
| Auto import issues | Pull agent findings on context menu |
Options
node src/index.js --port 9999 # Custom port (default: 9999)
node src/index.js --db /path/to/data.json # Persistence file (default: burpai-data.json)
node src/index.js --port 9001 --db custom.json
Data persists across restarts when --db is set (or by default). The server auto-saves on every mutation and loads data on startup.
Burp plugin URL configurable from the burpAI settings tab in Burp.
Requirements
- Node.js 18+
- Burp Suite (Community or Professional)
- Jython 2.7 standalone JAR (configured in Burp Extensions → Environment)
<p align="center"> <i>Built for AI-assisted penetration testing.</i> <br /> <samp>#burpsuite #mcp #pentest #bugbounty</samp> </p>
推荐服务器
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。
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。
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。
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。
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。
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。
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。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
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。