mcp_server_reuneMacacada MCP Server

MCP Server

A server that generates Master Content Plans (MCPs) based on topics. The server aggregates resources from the web and organizes them into structured learning paths.

Features

Generate learning paths for any topic (not just technology topics)
Find relevant resources using web search and scraping
Organize resources into a logical sequence with customizable number of nodes
Support for multiple languages with focus on Portuguese
Performance optimizations for Render's free tier
Caching system for faster responses
Return a standardized JSON structure for consumption by client applications
NEW: TF-IDF based resource relevance filtering to ensure resources match the requested topic
NEW: Strategic quiz distribution across learning trees for balanced learning experiences
NEW: YouTube integration to include relevant videos in learning paths
NEW: Category system to generate more specific content for different types of topics
NEW: Asynchronous task system with real-time progress feedback to improve user experience and avoid timeouts
NEW: Enhanced caching system for improved performance and faster response times
NEW: Optimized web scraping techniques for better resource utilization
NEW: Adaptive scraping system that automatically chooses the most efficient method for each website
NEW: Puppeteer instance pool for efficient browser reuse and reduced memory usage

Tech Stack

Python 3.9+
FastAPI
Pyppeteer for JavaScript-heavy web scraping
Pyppeteer-stealth for avoiding detection during web scraping
Puppeteer instance pool for efficient browser reuse
DuckDuckGo Search API
BeautifulSoup for HTML parsing
scikit-learn for TF-IDF based resource relevance filtering
yt-dlp for YouTube video search and metadata extraction
Redis (optional) for distributed caching
msgpack for efficient data serialization
cachetools for advanced in-memory caching

Installation

Clone the repository:

git clone https://github.com/yourusername/mcp_server.git
cd mcp_server

Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install Python dependencies:
```
pip install -r requirements.txt
```
Install Node.js dependencies (for the optimized scraping system):
```
npm install
```
Install Chrome/Chromium for Pyppeteer (if not already installed)

Usage

Running Locally

Start the server using the provided batch file (Windows):
```
run_local.bat
```
Or manually with uvicorn:
```
uvicorn main:app --reload --host 0.0.0.0 --port 8000
```
Access the API at http://localhost:8000
Generate an MCP by making a GET request to:
```
GET /generate_mcp?topic=your_topic
```
Check the API documentation at http://localhost:8000/docs

Production URL

The production server is available at:

https://reunemacacada.onrender.com

All endpoints documented in this README are available at both the local and production URLs.

Testing the Caching System

Make a first request to generate an MCP (this will populate the cache):
```
GET /generate_mcp?topic=python&num_nodes=15&language=pt
```
Make a second request with the same parameters (this should use the cache):
```
GET /generate_mcp?topic=python&num_nodes=15&language=pt
```
The second request should be significantly faster as the result will be retrieved from the cache.

Documentation

Detailed documentation is available in the docs folder:

API Reference - Detailed API documentation
Endpoints Reference - Complete reference of all endpoints
Flutter Integration - Guide for integrating with Flutter apps
Async Tasks System - Documentation for the asynchronous task system
Performance Improvements - Overview of performance optimizations
Caching System - Documentation for the caching system
Web Scraping Optimization - Details on web scraping optimizations

API Endpoints

GET /health - Health check endpoint
GET /generate_mcp?topic={topic}&max_resources={max_resources}&num_nodes={num_nodes}&min_width={min_width}&max_width={max_width}&min_height={min_height}&max_height={max_height}&language={language}&category={category} - Generate an MCP for the specified topic synchronously
- topic (required): The topic to generate an MCP for (minimum 3 characters)
- max_resources (optional): Maximum number of resources to include (default: 15, min: 5, max: 30)
- num_nodes (optional): Number of nodes to include in the learning path (default: 15, min: 10, max: 30)
- min_width (optional): Minimum width of the tree (nodes at first level) (default: 3, min: 2, max: 10)
- max_width (optional): Maximum width at any level of the tree (default: 5, min: 3, max: 15)
- min_height (optional): Minimum height of the tree (depth) (default: 3, min: 2, max: 8)
- max_height (optional): Maximum height of the tree (depth) (default: 7, min: 3, max: 12)
- language (optional): Language for resources (default: "pt")
- category (optional): Category for the topic (e.g., "technology", "finance", "health"). If not provided, it will be detected automatically.
POST /generate_mcp_async?topic={topic}&max_resources={max_resources}&num_nodes={num_nodes}&min_width={min_width}&max_width={max_width}&min_height={min_height}&max_height={max_height}&language={language}&category={category} - Start asynchronous generation of an MCP
GET /status/{task_id} - Check the status of an asynchronous task
GET /tasks - List all tasks
POST /clear_cache?pattern={pattern}&clear_domain_cache={clear_domain_cache} - Clear the cache based on a pattern
- pattern (optional): Pattern to match cache keys (default: "*" for all)
- clear_domain_cache (optional): Whether to also clear the domain method cache (default: false)
GET /cache_stats - Get statistics about the cache, including information about the domain method cache

Examples

Basic usage (Portuguese)

GET /generate_mcp?topic=python

Custom number of nodes

GET /generate_mcp?topic=machine+learning&num_nodes=20

English language

GET /generate_mcp?topic=javascript&language=en

Specify category manually

GET /generate_mcp?topic=python&category=technology

Full customization

GET /generate_mcp?topic=história+do+brasil&max_resources=20&num_nodes=25&min_width=4&max_width=8&min_height=4&max_height=8&language=pt

Control tree structure

GET /generate_mcp?topic=machine+learning&min_width=2&max_width=4&min_height=5&max_height=10

Asynchronous generation

POST /generate_mcp_async?topic=inteligência+artificial&category=technology

Check task status

GET /status/550e8400-e29b-41d4-a716-446655440000

Clear cache

POST /clear_cache

Clear specific cache

POST /clear_cache?pattern=mcp:*

Performance Improvements

The MCP Server includes several performance optimizations:

Caching System: Results are cached to improve response times for repeated queries
Asynchronous Task System: Long-running operations are handled asynchronously
Resource Filtering: TF-IDF based filtering to select the most relevant resources
Optimized Web Scraping: Efficient web scraping techniques to reduce resource usage
Adaptive Scraping System: Automatically chooses the most efficient scraping method for each website
Puppeteer Instance Pool: Reuses browser instances to reduce memory usage and startup time
Domain Method Cache: Remembers which scraping method works best for each domain
Resource Blocking: Blocks unnecessary resources (images, stylesheets, fonts) during scraping

Performance Gains

60-80% reduction in response time for topics already in cache
30-50% reduction in response time for new topics
40-60% reduction in memory usage during web scraping
3-5x increase in throughput for simultaneous requests

Deployment

The server can be deployed to various platforms:

Using Docker

docker build -t mcp-server .
docker run -p 8080:8080 mcp-server

Deploying to Render, Fly.io, or other platforms

Follow the platform-specific instructions for deploying a Docker container or a Python application.

License

This software is proprietary and confidential. Unauthorized copying, distribution, modification, public display, or public performance of this software is strictly prohibited. This software is intended for use under a paid subscription model only.

Last commit: v1.1.2 - Correção de problemas com DuckDuckGo rate limit e Puppeteer

MCP Server

A server that generates Master Content Plans (MCPs) based on topics. The server aggregates resources from the web and organizes them into structured learning paths.

Features

Generate learning paths for any topic (not just technology topics)
Find relevant resources using web search and scraping
Organize resources into a logical sequence with customizable number of nodes
Support for multiple languages with focus on Portuguese
Performance optimizations for Render's free tier
Caching system for faster responses
Return a standardized JSON structure for consumption by client applications
NEW: TF-IDF based resource relevance filtering to ensure resources match the requested topic
NEW: Strategic quiz distribution across learning trees for balanced learning experiences
NEW: YouTube integration to include relevant videos in learning paths
NEW: Category system to generate more specific content for different types of topics
NEW: Asynchronous task system with real-time progress feedback to improve user experience and avoid timeouts
NEW: Enhanced caching system for improved performance and faster response times
NEW: Optimized web scraping techniques for better resource utilization
NEW: Adaptive scraping system that automatically chooses the most efficient method for each website
NEW: Puppeteer instance pool for efficient browser reuse and reduced memory usage

Tech Stack

Python 3.9+
FastAPI
Pyppeteer for JavaScript-heavy web scraping
Pyppeteer-stealth for avoiding detection during web scraping
Puppeteer instance pool for efficient browser reuse
DuckDuckGo Search API
BeautifulSoup for HTML parsing
scikit-learn for TF-IDF based resource relevance filtering
yt-dlp for YouTube video search and metadata extraction
Redis (optional) for distributed caching
msgpack for efficient data serialization
cachetools for advanced in-memory caching

Installation

Clone the repository:

git clone https://github.com/yourusername/mcp_server.git
cd mcp_server

Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install Python dependencies:
```
pip install -r requirements.txt
```
Install Node.js dependencies (for the optimized scraping system):
```
npm install
```
Install Chrome/Chromium for Pyppeteer (if not already installed)

Usage

Running Locally

Start the server using the provided batch file (Windows):
```
run_local.bat
```
Or manually with uvicorn:
```
uvicorn main:app --reload --host 0.0.0.0 --port 8000
```
Access the API at http://localhost:8000
Generate an MCP by making a GET request to:
```
GET /generate_mcp?topic=your_topic
```
Check the API documentation at http://localhost:8000/docs

Production URL

The production server is available at:

https://reunemacacada.onrender.com

All endpoints documented in this README are available at both the local and production URLs.

Testing the Caching System

Make a first request to generate an MCP (this will populate the cache):
```
GET /generate_mcp?topic=python&num_nodes=15&language=pt
```
Make a second request with the same parameters (this should use the cache):
```
GET /generate_mcp?topic=python&num_nodes=15&language=pt
```
The second request should be significantly faster as the result will be retrieved from the cache.

Documentation

Detailed documentation is available in the docs folder:

API Reference - Detailed API documentation
Endpoints Reference - Complete reference of all endpoints
Flutter Integration - Guide for integrating with Flutter apps
Async Tasks System - Documentation for the asynchronous task system
Performance Improvements - Overview of performance optimizations
Caching System - Documentation for the caching system
Web Scraping Optimization - Details on web scraping optimizations

API Endpoints

GET /health - Health check endpoint
GET /generate_mcp?topic={topic}&max_resources={max_resources}&num_nodes={num_nodes}&min_width={min_width}&max_width={max_width}&min_height={min_height}&max_height={max_height}&language={language}&category={category} - Generate an MCP for the specified topic synchronously
- topic (required): The topic to generate an MCP for (minimum 3 characters)
- max_resources (optional): Maximum number of resources to include (default: 15, min: 5, max: 30)
- num_nodes (optional): Number of nodes to include in the learning path (default: 15, min: 10, max: 30)
- min_width (optional): Minimum width of the tree (nodes at first level) (default: 3, min: 2, max: 10)
- max_width (optional): Maximum width at any level of the tree (default: 5, min: 3, max: 15)
- min_height (optional): Minimum height of the tree (depth) (default: 3, min: 2, max: 8)
- max_height (optional): Maximum height of the tree (depth) (default: 7, min: 3, max: 12)
- language (optional): Language for resources (default: "pt")
- category (optional): Category for the topic (e.g., "technology", "finance", "health"). If not provided, it will be detected automatically.
POST /generate_mcp_async?topic={topic}&max_resources={max_resources}&num_nodes={num_nodes}&min_width={min_width}&max_width={max_width}&min_height={min_height}&max_height={max_height}&language={language}&category={category} - Start asynchronous generation of an MCP
GET /status/{task_id} - Check the status of an asynchronous task
GET /tasks - List all tasks
POST /clear_cache?pattern={pattern}&clear_domain_cache={clear_domain_cache} - Clear the cache based on a pattern
- pattern (optional): Pattern to match cache keys (default: "*" for all)
- clear_domain_cache (optional): Whether to also clear the domain method cache (default: false)
GET /cache_stats - Get statistics about the cache, including information about the domain method cache

Examples

Basic usage (Portuguese)

GET /generate_mcp?topic=python

Custom number of nodes

GET /generate_mcp?topic=machine+learning&num_nodes=20

English language

GET /generate_mcp?topic=javascript&language=en

Specify category manually

GET /generate_mcp?topic=python&category=technology

Full customization

GET /generate_mcp?topic=história+do+brasil&max_resources=20&num_nodes=25&min_width=4&max_width=8&min_height=4&max_height=8&language=pt

Control tree structure

GET /generate_mcp?topic=machine+learning&min_width=2&max_width=4&min_height=5&max_height=10

Asynchronous generation

POST /generate_mcp_async?topic=inteligência+artificial&category=technology

Check task status

GET /status/550e8400-e29b-41d4-a716-446655440000

Clear cache

POST /clear_cache

Clear specific cache

POST /clear_cache?pattern=mcp:*

Performance Improvements

The MCP Server includes several performance optimizations:

Caching System: Results are cached to improve response times for repeated queries
Asynchronous Task System: Long-running operations are handled asynchronously
Resource Filtering: TF-IDF based filtering to select the most relevant resources
Optimized Web Scraping: Efficient web scraping techniques to reduce resource usage
Adaptive Scraping System: Automatically chooses the most efficient scraping method for each website
Puppeteer Instance Pool: Reuses browser instances to reduce memory usage and startup time
Domain Method Cache: Remembers which scraping method works best for each domain
Resource Blocking: Blocks unnecessary resources (images, stylesheets, fonts) during scraping

Performance Gains

60-80% reduction in response time for topics already in cache
30-50% reduction in response time for new topics
40-60% reduction in memory usage during web scraping
3-5x increase in throughput for simultaneous requests

Deployment

The server can be deployed to various platforms:

Using Docker

docker build -t mcp-server .
docker run -p 8080:8080 mcp-server

Deploying to Render, Fly.io, or other platforms

Follow the platform-specific instructions for deploying a Docker container or a Python application.

License

Last commit: v1.1.2 - Correção de problemas com DuckDuckGo rate limit e Puppeteer

MCP Server

README Documentation

MCP Server

Features

Tech Stack

Installation

Usage

Running Locally

Production URL

Testing the Caching System

Documentation

API Endpoints

Examples

Basic usage (Portuguese)

Custom number of nodes

English language

Specify category manually

Full customization

Control tree structure

Asynchronous generation

Check task status

Clear cache

Clear specific cache

Performance Improvements

Performance Gains

Deployment

Using Docker

Deploying to Render, Fly.io, or other platforms

License

Quick Actions

Key Features

MCP Server

README Documentation

MCP Server

Features

Tech Stack

Installation

Usage

Running Locally

Production URL

Testing the Caching System

Documentation

API Endpoints

Examples

Basic usage (Portuguese)

Custom number of nodes

English language

Specify category manually

Full customization

Control tree structure

Asynchronous generation

Check task status

Clear cache

Clear specific cache

Performance Improvements

Performance Gains

Deployment

Using Docker

Deploying to Render, Fly.io, or other platforms

License

Quick Actions

Key Features