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WebScout MCP is a powerful Model Context Protocol (MCP) server designed for reverse engineering web applications, particularly chat interfaces and streaming APIs. It provides comprehensive browser…

Publisherpyscout
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LanguageJavaScript
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  • Connect tools to AI workflows

    WebScout exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 14 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

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    1 stars and 2 forks from the linked repository.

πŸ” WebScout MCP

License: ISC Node.js Version MCP SDK

WebScout MCP is a powerful Model Context Protocol (MCP) server designed for reverse engineering web applications, particularly chat interfaces and streaming APIs. It provides comprehensive browser automation tools to discover, analyze, and capture network traffic from complex web applications.

✨ Key Features

πŸ€– Automated Reverse Engineering

  • One-Click Analysis: Automatically navigate to web applications and capture streaming endpoints
  • Smart Pattern Detection: Advanced detection of SSE, WebSocket, chunked transfers, and custom streaming formats
  • Network Traffic Capture: Comprehensive CDP-level monitoring of all HTTP requests, responses, and WebSocket frames
  • Structured Data Output: Clean, parsed data with URLs, request payloads, and response patterns

πŸ” Interactive Browser Automation

  • Session Management: Persistent browser sessions with cookie and authentication state management
  • Authentication Support: Handle login forms, OAuth flows, and multi-factor authentication
  • Step-by-Step Navigation: Click buttons, fill forms, and navigate through complex multi-page interfaces
  • Visual Feedback: Take screenshots at any point to understand page state and UI elements

🎯 Advanced Network Monitoring

  • Real-Time Capture: Monitor streaming responses as they occur with configurable capture windows
  • Flexible Filtering: Capture all traffic or filter by POST requests, streaming responses, or URL patterns
  • WebSocket Support: Full capture of WebSocket frames, messages, and connection details
  • Memory Management: Configurable capture limits to prevent memory issues during long sessions

πŸ› οΈ Developer-Friendly Tools

  • 14 Specialized Tools: Comprehensive toolkit for web scraping, testing, and API discovery
  • Headless or Visible: Run in headless mode for automation or visible mode for debugging
  • Error Handling: Robust error handling with detailed error messages and recovery options
  • Cross-Platform: Works on macOS, Linux, and Windows with consistent behavior

πŸ“‹ Available Tools

Core Reverse Engineering

  • reverse_engineer_chat - Automated analysis of chat interfaces with streaming endpoint discovery
  • start_network_capture - Begin comprehensive network traffic monitoring
  • stop_network_capture - End capture and retrieve all collected data
  • get_network_capture_status - Check capture session status and statistics
  • clear_network_capture - Clear captured data without stopping the capture session

Interactive Browser Control

  • initialize_session - Create a new browser session for interactive operations
  • close_session - Clean up browser resources and end session
  • navigate_to_url - Navigate to different URLs within a session
  • switch_tab - Switch between open browser tabs

User Interaction Simulation

  • click_element - Click buttons, links, or any interactive elements
  • fill_form - Fill out form fields with automatic submission options
  • wait_for_element - Wait for dynamic elements to appear before continuing

Visual Inspection

  • take_screenshot - Capture screenshots of viewport, full page, or specific elements
  • get_current_page_info - Retrieve comprehensive page information and tab details

πŸš€ Installation

Prerequisites

  • Node.js 18+ - Required for ES modules and modern JavaScript features
  • npm - Package manager for dependency installation

Quick Setup

bash
# Clone the repository
git clone https://github.com/pyscout/webscout-mcp
cd webscout-mcp

# Install dependencies
npm install

# Install Playwright browsers for automation
npx playwright install

πŸ“– Usage

Method 1: MCP Server (Recommended)

Add WebScout MCP to your MCP client configuration:

json
{
  "mcpServers": {
    "webscout-mcp": {
      "command": "npx",
      "args": ["-y", "webscout-mcp"]
    }
  }
}

Method 2: Direct CLI Usage

bash
# Start the MCP server directly
npm start

# Or run with node
node src/index.js

Method 3: Development Mode

bash
# Run with visible browser for debugging
node src/index.js  # Set headless: false in session initialization

πŸ› οΈ API Examples

Basic Chat Interface Analysis

javascript
// Initialize session and analyze a chat interface
const session = await initializeSession("https://chat.example.com");
const analysis = await reverseEngineerChat("https://chat.example.com", "Hello", 8000);

console.log("Found endpoints:", analysis.length);
await closeSession(session.sessionId);

Interactive Login Flow

javascript
// Handle login and navigate to protected content
const session = await initializeSession("https://app.example.com/login");

await fillForm(session.sessionId, [
  { selector: 'input[name="email"]', value: "user@example.com" },
  { selector: 'input[name="password"]', value: "password123" }
], 'button[type="submit"]');

await waitForElement(session.sessionId, ".dashboard", 10000);
const screenshot = await takeScreenshot(session.sessionId);

await closeSession(session.sessionId);

Network Traffic Capture

javascript
// Monitor all network activity on a page
const session = await initializeSession("https://api.example.com");

await startNetworkCapture(session.sessionId, {
  capturePostOnly: false,
  captureStreaming: true,
  maxCaptures: 100
});

// Perform actions that generate network traffic
await navigateToUrl(session.sessionId, "https://api.example.com/data");

const captureData = await stopNetworkCapture(session.sessionId);
console.log("Captured requests:", captureData.data.requests.length);

await closeSession(session.sessionId);

πŸ—οΈ Architecture Overview

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚ Chat Interface  │───▢│ Browser Automation│───▢│ Network Capture β”‚
β”‚  (Target URL)   β”‚    β”‚   (Playwright)    β”‚    β”‚  (CDP + Route)  β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
         β”‚                       β”‚                       β”‚
         β–Ό                       β–Ό                       β–Ό
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  Message Input  β”‚    β”‚  DOM Interaction  β”‚    β”‚ Request/Responseβ”‚
β”‚   Detection     β”‚    β”‚    (Auto-fill)    β”‚    β”‚    Analysis     β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                                                       β”‚
                                                       β–Ό
                                            β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
                                            β”‚ Structured Data β”‚
                                            β”‚  Output (JSON)  β”‚
                                            β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Workflow

  1. Browser Launch: Opens target URL in headless Playwright browser
  2. Network Setup: Establishes Chrome DevTools Protocol (CDP) session and route interception
  3. Interface Detection: Automatically locates chat input elements (textarea, contenteditable, etc.)
  4. Message Injection: Sends test message to trigger streaming responses
  5. Traffic Capture: Monitors network requests/responses for specified time window
  6. Pattern Analysis: Identifies streaming patterns in captured data
  7. Data Processing: Structures captured data into clean JSON format

Streaming Detection Patterns

The system detects multiple streaming response formats:

  • Server-Sent Events (SSE): data: {"content": "..."}
  • OpenAI-style chunks: data: {"choices": [{"delta": {"content": "..."}}]}
  • Event streams: event: message\ndata: {...}
  • JSON streaming: Objects with token, delta, content fields
  • Custom formats: f:{...}, 0:"...", e:{...} patterns
  • WebSocket messages: Binary/text frames with streaming data
  • Chunked responses: Transfer-encoding: chunked with streaming content

πŸ“ Project Structure

webscout-mcp/
β”œβ”€β”€ src/
β”‚   β”œβ”€β”€ index.js                 # Main MCP server implementation
β”‚   └── tools/                   # Specialized tool modules
β”‚       β”œβ”€β”€ reverseEngineer.js   # Tool exports and coordination
β”‚       β”œβ”€β”€ reverseEngineerChat.js # Automated chat analysis
β”‚       β”œβ”€β”€ sessionManagement.js # Browser session lifecycle
β”‚       β”œβ”€β”€ visualInspection.js  # Screenshots and page info
β”‚       β”œβ”€β”€ interaction.js       # Clicking and form filling
β”‚       β”œβ”€β”€ navigation.js        # URL navigation and tab switching
β”‚       └── networkCapture.js    # Network traffic monitoring
β”‚   └── utilities/               # Shared utility functions
β”‚       β”œβ”€β”€ browser.js           # Browser automation utilities
β”‚       └── network.js           # Network pattern detection
β”œβ”€β”€ package.json                 # Dependencies and scripts
β”œβ”€β”€ mcp-config.json              # MCP client configuration example
└── README.md                    # This documentation

πŸ”§ Configuration

Environment Variables

VariableDescriptionDefault
NODE_ENVEnvironment modedevelopment
DEBUGEnable debug loggingfalse

MCP Configuration

Update your MCP client's configuration file:

json
{
  "mcpServers": {
    "webscout-mcp": {
      "command": "npx",
      "args": ["-y", "webscout-mcp"],
      "env": {
        "NODE_ENV": "production"
      }
    }
  }
}

Or for VS Code MCP configuration (mcp.json):

json
{
  "servers": {
    "webscout-mcp": {
      "command": "npx",
      "args": ["-y", "webscout-mcp"],
      "type": "stdio"
    }
  }
}

Contributing

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature-name
  3. Make your changes and add tests
  4. Run tests: npm test
  5. Submit a pull request

Development Guidelines

  • Follow ES6+ syntax and modern JavaScript practices
  • Add JSDoc comments for new functions
  • Test your changes with multiple chat interfaces
  • Update documentation for new features
  • Ensure code passes all tests

πŸ“„ License

This project is licensed under the ISC License - see the LICENSE file for details.

πŸ™ Acknowledgments

⚠️ Important Notes

  • Ethical Use: This tool is intended for API analysis and integration purposes only. Always respect website terms of service and robots.txt files.
  • Rate Limiting: Some chat interfaces may have rate limits or CAPTCHAs that could interfere with analysis.
  • Browser Dependencies: Playwright requires browser binaries to be installed for automation.
  • Network Conditions: Results may vary based on network speed and target website performance.

πŸ› Troubleshooting

Common Issues

"Browser not found" error

bash
# Install Playwright browsers
npx playwright install

"Connection timeout" error

  • Increase captureWindowMs parameter
  • Check network connectivity
  • Verify target URL is accessible

"No streaming endpoints found"

  • Try different test messages
  • Increase capture window time
  • Verify the chat interface doesn't require authentication

MCP connection issues

  • Verify the absolute path in mcp-config.json
  • Ensure Node.js 18+ is installed
  • Check MCP client logs for detailed errors

πŸ“ž Support

If you encounter issues or have questions:

  1. Check the Troubleshooting section
  2. Review existing Issues on GitHub
  3. Create a new Issue with detailed information

WebScout MCP - Your intelligent companion for web application reverse engineering and API discovery.

Made with ❀️ for developers, security researchers, and API enthusiasts

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "webscout-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "webscout-mcp"
      ]
    }
  }
}

Available Tools

  • reverse_engineer_chat

    Automatically reverse engineer a chat interface by navigating to the URL, sending a test message, and capturing all network traffic to identify streaming API endpoints. Returns discovered endpoints with their request/response patterns including Server-Sent Events (SSE), WebSocket connections, and chunked HTTP responses. Perfect for quick analysis of public chat interfaces without authentication.

  • initialize_session

    Create a persistent browser session for step-by-step reverse engineering of complex chat interfaces. Use this when the chat requires login, multi-step navigation, or manual interaction before analysis. Returns a sessionId that must be used with all subsequent interactive tools. The session maintains cookies, authentication state, and can be used across multiple operations until explicitly closed.

  • take_screenshot

    Capture a screenshot of the current browser page as a base64-encoded PNG image. Essential for visual feedback to understand what's displayed before deciding which buttons to click or forms to fill. Supports capturing the visible viewport, entire scrollable page, or specific elements. Returns the image as base64 string and data URL for easy display.

  • click_element

    Click a button, link, or any interactive element on the page. Useful for navigating through multi-step interfaces, opening chat modals, starting new conversations, or triggering UI actions. Can target elements by CSS selector or by their visible text content. Automatically waits after clicking to allow page updates.

  • fill_form

    Fill out one or multiple form fields in sequence, perfect for login forms, registration, search inputs, or any text entry. Supports pressing Enter after each field and clicking a submit button. Commonly used for authentication flows before accessing chat interfaces. Each field can be filled independently with optional Enter key press.

  • switch_tab

    Switch the active browser tab when multiple tabs are open in the session. Common scenario: clicking a link that opens a chat in a new tab requires switching to that tab to interact with it. Use get_current_page_info first to see all available tabs and their indices.

  • navigate_to_url

    Navigate to a different URL within the same browser session. Maintains all cookies, authentication state, and session data. Useful for moving between different sections of a website (e.g., from login page to chat page, or from homepage to a specific conversation URL). Supports different wait strategies for page load completion.

  • wait_for_element

    Wait for a specific element to appear on the page before continuing. Essential for handling dynamic content that loads asynchronously, page transitions, or elements that appear after clicking buttons. Prevents errors from trying to interact with elements that haven't loaded yet. Commonly used after login, navigation, or clicking buttons that trigger loading states.

  • get_current_page_info

    Retrieve comprehensive information about the current browser state including current URL, page title, number of open tabs, and details about each tab. Essential for understanding where you are in a multi-step process, confirming navigation worked, or deciding which tab to switch to. Returns list of all tabs with their URLs, titles, and which one is currently active.

  • close_session

    Close the browser session and free all associated resources including browser instance, pages, and contexts. Always call this when finished with a session to prevent memory leaks. The sessionId becomes invalid after closing and cannot be reused. Any unsaved work or open pages will be lost.

  • start_network_capture

    Start capturing network traffic on the current browser session. Monitors all HTTP requests and responses, WebSocket frames, and streaming data. Can filter by POST requests only, streaming responses only, or specific URL patterns. Essential for analyzing API calls, debugging network issues, or monitoring real-time data flows.

  • stop_network_capture

    Stop the active network capture session and return all captured data. Returns comprehensive network traffic including requests, responses, WebSocket frames, and streaming data with timestamps and headers. Use this to analyze captured network activity or save data for later processing.

  • get_network_capture_status

    Get the current status of network capture for a session. Returns whether capture is active, duration, current statistics, and capture options. Useful for monitoring capture progress or checking if capture is running before stopping.

  • clear_network_capture

    Clear all captured network data without stopping the capture session. Resets request/response buffers while keeping capture active. Useful for long-running captures where you want to periodically clear old data to prevent memory issues.

Use WebScout MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once WebScout is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add WebScout as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the WebScout MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "webscout": {
      "command": "npx",
      "args": [
        "-y",
        "webscout-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the WebScout MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the WebScout MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use WebScout to help me with this task?
WebScout
Sure. I read it.
Here is what I found using WebScout.

Frequently asked questions

What is the WebScout MCP server used for?

WebScout is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use WebScout MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use WebScout with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use WebScout MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With WebScout connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect WebScout MCP to TypingMind?

WebScout runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does WebScout MCP provide in TypingMind?

WebScout exposes 14 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use WebScout MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If WebScout requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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