🌐 Amazon Q Web Documentation Reader

MCP Server for Intelligent Web Content Extraction

Features • Installation • Setup • Usage • Tools

✨ Features

• 🧠 Intelligent Navigation - Amazon Q (Claude 4.5) decides which documentation pages to visit

• 🧹 Clean Content Extraction - Removes navigation, ads, scripts, and other non-content elements

• 📝 Multiple Output Formats - Supports both Markdown and plain text output

• 💻 Code Block Extraction - Specifically extracts code examples from documentation

• 📊 Page Structure Analysis - Extracts heading hierarchy and table of contents

• 🔗 Link Discovery - Finds and filters documentation links

• 📚 Batch Processing - Read multiple documentation pages at once

🎯 How It Works

📦 Installation

Prerequisites

• Python 3.12 or higher

• uv (recommended) or pip

• Amazon Q CLI

Step 1: Clone the Repository

Step 2: Install Dependencies

Using uv (Recommended):

Using pip:

🔧 Setup with Amazon Q

Step 1: Locate Your MCP Configuration File

Amazon Q looks for MCP server configuration in:

• Linux/WSL: ~/.aws/amazonq/mcp.json

• macOS: ~/.aws/amazonq/mcp.json

• Windows: %USERPROFILE%\.aws\amazonq\mcp.json

Step 2: Create/Edit the Configuration File

Create the directory if it doesn't exist:

Edit or create ~/.aws/amazonq/mcp.json:

For Linux/WSL:

For macOS:

For Windows:

💡 Tip: Replace /full/path/to/ with the actual path where you cloned the repository.

Step 3: Verify Installation

1. Start Amazon Q CLI:

   q chat

2. Check if MCP server is loaded:

   /mcp

   You should see:

   doc_reader - read_web_documentation - get_documentation_links - get_page_structure - extract_code_examples - read_multiple_docs

3. If not loaded:

   • Check the file path in mcp.json is correct

   • Restart Amazon Q CLI

   • Check logs: q chat logdump

🚀 Usage

Basic Example

In Amazon Q CLI, simply ask about documentation:

Amazon Q will:

1. ✅ Read the main documentation page

2. ✅ Extract all available links

3. ✅ Intelligently identify the "Routes" link

4. ✅ Navigate to the Routes documentation

5. ✅ Provide you with accurate information

More Examples

Python Documentation:

FastAPI Tutorial:

AWS Lambda:

🛠 Available Tools

Amazon Q intelligently chains these tools to navigate documentation:

1. read_web_documentation

Fetches and extracts clean documentation content from a web page.

Parameters:

• url (required): The URL of the documentation page

• output_format (optional): "markdown" (default) or "text"

Returns: Extracted documentation content with title and metadata

2. get_documentation_links

Extracts all links from a documentation page with optional filtering.

Parameters:

• url (required): The URL of the documentation page

• filter_pattern (optional): Pattern to filter links (e.g., "api", "guide")

Returns: List of links found on the page

3. get_page_structure

Extracts the heading structure and table of contents from a documentation page.

Parameters:

• url (required): The URL of the documentation page

Returns: Hierarchical structure of headings on the page

4. extract_code_examples

Extracts all code blocks from a documentation page.

Parameters:

• url (required): The URL of the documentation page

Returns: All code blocks found with their detected languages

5. read_multiple_docs

Reads multiple documentation pages and combines their content.

Parameters:

• urls (required): List of documentation URLs (max 10)

Returns: Combined content from all pages

📁 Project Structure

⚙️ Configuration

Edit src/config.py to customize behavior:

🐛 Troubleshooting

MCP Server Not Loading

Check configuration:

Verify paths are correct:

• Use absolute paths, not relative

• Check that Python executable exists

• Check that main.py exists

Test server manually:

Check Amazon Q logs:

Server Starts But Tools Don't Work

Verify dependencies are installed:

Reinstall dependencies:

Connection Timeout

Increase timeout in settings:

📚 Dependencies

⚠️ Limitations

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository

2. Create your feature branch (git checkout -b feature/AmazingFeature)

3. Commit your changes (git commit -m 'Add some AmazingFeature')

4. Push to the branch (git push origin feature/AmazingFeature)

5. Open a Pull Request

📄 License

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

💬 Support

• 📫 Open an Issue for bug reports or feature requests

• ⭐ Star this repo if you find it useful!