MCP server for working with AWS Blog and News articles

Created By

mirecekd6 months ago

This MCP server provides tools for retrieving and filtering AWS blog articles and news from all AWS categories. The server is built using the FastMCP framework and supports SSE transport on port 8807.

# awsblogs

# mcp

Overview Content Tools Comments

Content

AWS Blogs MCP Server

MCP server for working with AWS Blog and News articles from api.aws-news.com.

Description

Available MCP Tools

1. `get_todays_posts`

Gets articles published today.

Parameters:

post_type: "News", "Blog", or "Both" (default)
limit: Maximum number of articles (default 20)

2. `get_posts_by_date`

Gets articles from a specific date range.

Parameters:

from_date: From date in YYYY-MM-DD format (optional)
to_date: To date in YYYY-MM-DD format (optional)
days_back: Number of days back from today (alternative to from_date)
post_type: "News", "Blog", or "Both" (default)
limit: Maximum number of articles (default 50)

3. `get_posts_by_category`

Gets articles from a specific category.

Parameters:

category: Category name (e.g., "Big Data", "Machine Learning", "Industries")
post_type: "News", "Blog", or "Both" (default)
days_back: Number of days back from today (default 30)
limit: Maximum number of articles (default 30)

4. `search_posts`

Searches articles by text query.

Parameters:

query: Search query (searches in title, URL, and slug)
post_type: "News", "Blog", or "Both" (default)
days_back: Number of days back from today (default 90)
limit: Maximum number of articles (default 25)

5. `get_categories`

Gets a list of all available article categories.

6. `get_latest_posts`

Gets the latest articles.

Parameters:

post_type: "News", "Blog", or "Both" (default)
limit: Maximum number of articles (default 20)
days_back: Number of days back from today (default 7)

7. `get_popular_posts`

Gets popular articles (marked as popular=true).

Parameters:

post_type: "News", "Blog", or "Both" (default)
days_back: Number of days back from today (default 30)
limit: Maximum number of articles (default 15)

8. `get_article_content`

Downloads full article content from a given URL.

Parameters:

url: Article URL (can be obtained from other tools)

Return values:

title: Article title
content: Full article text
description: Meta description
author: Author (if available)
published_date: Publication date
content_length: Content length in characters
word_count: Word count

Available Categories

The server supports filtering by these categories:

Architecture
AWS Cloud Operations
AWS for Games
AWS Insights
AWS Marketplace
AWS News
AWS Partner Network
AWS Smart Business
Big Data
Business Intelligence
Business Productivity
Cloud Enterprise Strategy
Cloud Financial Management
Compute
Contact Center
Containers
Database
Desktop & Application Streaming
Developer Tools
DevOps & Developer Productivity
Front-End Web & Mobile
HPC
IBM and Red Hat
Industries
Integration & Automation
Internet of Things
Machine Learning
Media
Messaging & Targeting
Microsoft Workloads on AWS
Migration and Modernization
.NET on AWS
Networking & Content Delivery
Open Source
Public Sector
Quantum Computing
SAP
Security
Spatial Computing
Startups
Storage
Supply Chain & Logistics
Training & Certification

Installation and Running

Docker (recommended)

Run from GitHub Container Registry:

docker run -p 8807:8807 ghcr.io/mirecekd/awsblogs-mcp

Build Docker image locally:
```
chmod +x build.sh
./build.sh
```
Run using docker-compose:
```
docker-compose up awsblogs-mcp-sse
```

Or local Docker build:

docker run -p 8807:8807 awsblogs-mcp-server:sse

Local Development

Install dependencies:
```
pip install -e .
```

Run server:

python main_sse.py --host 0.0.0.0 --port 8807

MCP Client Configuration

To use in an MCP client (e.g., Cline), add to configuration:

{
  "mcpServers": {
    "awsblogs": {
      "type": "sse",
      "url": "http://localhost:8807/sse/"
    }
  }
}

API Endpoint

The server uses the public API: https://api.aws-news.com/articles

Features

✅ SSE transport on port 8807
✅ Filter by article type (News/Blog)
✅ Filter by category
✅ Date filtering (date range, days back)
✅ Text search
✅ Cache mechanism (5 minutes)
✅ Structured responses
✅ Docker support

Project Structure

awsblogs-mcp/
├── src/awsblogs_mcp_server/
│   ├── __init__.py
│   ├── server_sse.py          # SSE MCP server
│   └── data_processor.py      # API client and data processing
├── main_sse.py               # SSE entry point
├── Dockerfile.sse            # Docker image for SSE
├── docker-compose.yml        # Docker Compose configuration
├── build.sh                  # Build script
├── pyproject.toml            # Python project configuration
└── README.md                 # This file

Development

For development we recommend:

Fork the repository
Create a new branch for the feature
Test locally using python main_sse.py
Test Docker build using ./build.sh
Create a pull request

License

MIT License - see LICENSE file.

Author

Miroslav Dvořák (mirecekd@gmail.com)

Usage Examples

N8N Workflow Integration

This MCP server can be easily integrated with N8N workflows for automated AWS news processing and notifications.

AWS Blogs MCP in N8N

The screenshot above shows a real-world N8N workflow where the AWS Blogs MCP server is used as a tool within an AI Agent. The workflow consists of:

Chat Trigger - Receives user messages
AI Agent - Processes requests using Azure OpenAI
AWS Blogs MCP Tool - Fetches AWS articles based on user queries
Memory Buffer - Maintains conversation context

Example N8N Workflow: You can find a complete N8N workflow configuration in ./assets/n8n-workflow.json

How it works in practice:

User asks: "Show me latest AWS articles about Machine Learning"
AI Agent uses the MCP server to call search_posts with query "Machine Learning"
Server returns relevant AWS ML articles with titles, URLs, and summaries
AI Agent formats the response for the user with clickable links
Conversation context is maintained for follow-up questions

This integration allows for natural language interactions with AWS content, making it easy to stay updated with the latest AWS developments through conversational AI.