aws-content-mcp 0.1.0

MCP server for retrieving and analyzing AWS content from aws.amazon.com

AWS Content MCP Server

A comprehensive Model Context Protocol (MCP) server for retrieving and analyzing content from aws.amazon.com. This server provides dynamic, real-time access to AWS blogs, product information, solutions, pricing, and other content without hallucination.

Features

• Dynamic Content Retrieval: Real-time fetching from aws.amazon.com
• Comprehensive Search: Search across blogs, products, solutions, and pricing
• Full Content Analysis: Extract complete content with detailed analysis
• Duplicate Detection: Identify similar content and prevent duplication
• Content Comparison: Compare different AWS content pieces
• Service Overview: Get comprehensive AWS service listings
• No Hallucination: All information is fetched directly from AWS sources

Installation

Using uvx (Recommended)

uvx aws-content-mcp

Using pip

pip install aws-content-mcp

From Source

git clone https://github.com/yourusername/aws-content-mcp.git
cd aws-content-mcp
pip install -e .

Usage

As MCP Server

Add to your MCP client configuration:

{
  "mcpServers": {
    "aws-content": {
      "command": "uvx",
      "args": ["aws-content-mcp"]
    }
  }
}

Available Tools

1. search_aws_content

Search for AWS content across different categories.

Parameters:

• query (required): Search query
• content_type (optional): "all", "blogs", "products", "solutions", or "pricing"

Example:

{
  "query": "serverless computing",
  "content_type": "blogs"
}

2. get_full_aws_content

Get complete content from a specific AWS URL with detailed analysis.

Parameters:

• url (required): AWS URL to fetch content from

Example:

{
  "url": "https://aws.amazon.com/blogs/compute/serverless-computing-with-lambda/"
}

3. analyze_aws_blog_ideas

Analyze blog ideas for duplication and provide content recommendations.

Parameters:

• topic (required): Blog topic to analyze
• check_duplicates (optional): Whether to check for duplicates (default: true)

Example:

{
  "topic": "machine learning on AWS",
  "check_duplicates": true
}

4. get_aws_service_overview

Get comprehensive overview of all AWS services organized by category.

Parameters: None

5. compare_aws_content

Compare two pieces of AWS content for similarity and differences.

Parameters:

• url1 (required): First AWS URL to compare
• url2 (required): Second AWS URL to compare

Use Cases

1. Content Research

• Research AWS services and solutions
• Find relevant blog posts and documentation
• Get pricing information for AWS services

2. Blog Content Planning

• Check for duplicate blog ideas
• Analyze existing content on topics
• Get recommendations for unique angles

3. Competitive Analysis

• Compare different AWS solutions
• Analyze content similarities
• Track AWS product updates

4. Documentation Discovery

• Find comprehensive service documentation
• Discover best practices and guides
• Access latest AWS announcements

Architecture

The MCP server consists of several key components:

Content Fetcher (content_fetcher.py)

• Handles HTTP requests to aws.amazon.com
• Parses HTML content using BeautifulSoup
• Extracts clean content using readability
• Implements caching for performance
• Provides content similarity analysis

Server (server.py)

• Implements MCP protocol
• Defines available tools and their schemas
• Handles tool execution and error management
• Formats responses for optimal readability

Technical Details

Dependencies

• mcp: Model Context Protocol implementation
• httpx: Async HTTP client for web requests
• beautifulsoup4: HTML parsing and content extraction
• readability-lxml: Main content extraction
• markdownify: HTML to Markdown conversion
• pydantic: Data validation and serialization

Content Processing Pipeline

1. Search: Query AWS website sections
2. Extract: Use readability to get main content
3. Parse: Structure content with BeautifulSoup
4. Clean: Remove navigation, ads, and scripts
5. Format: Convert to Markdown for better readability
6. Cache: Store results for performance

Error Handling

• Comprehensive error catching and logging
• Graceful degradation for network issues
• Informative error messages for users
• Retry logic for transient failures

Development

Setup Development Environment

git clone https://github.com/yourusername/aws-content-mcp.git
cd aws-content-mcp
pip install -e ".[dev]"

Running Tests

pytest

Code Formatting

black src/
isort src/

Type Checking

mypy src/

Publishing to PyPI

Build Package

python -m build

Upload to PyPI

python -m twine upload dist/*

Configuration

The server can be configured through environment variables:

• AWS_CONTENT_CACHE_TTL: Cache time-to-live in seconds (default: 3600)
• AWS_CONTENT_MAX_RESULTS: Maximum search results (default: 20)
• AWS_CONTENT_TIMEOUT: HTTP request timeout (default: 30)

Limitations

• Only works with publicly accessible aws.amazon.com content
• Rate limited by AWS website response times
• Content structure may change as AWS updates their website
• Some dynamic content may not be fully captured

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Submit a pull request

License

MIT License - see LICENSE file for details.

Support

For issues and questions:

• GitHub Issues: https://github.com/yourusername/aws-content-mcp/issues
• Documentation: https://github.com/yourusername/aws-content-mcp/wiki

Changelog

v0.1.0

• Initial release
• Basic content fetching and search
• Blog analysis and duplicate detection
• Service overview functionality
• Content comparison tools