MCP Server
by MCP-Mirror
The MCP Server generates Master Content Plans (MCPs) based on topics. It aggregates resources from the web and organizes them into structured learning paths.
Last updated: N/A
What is MCP Server?
The MCP Server is a tool that automatically creates structured learning paths for any given topic. It utilizes web scraping and search to gather relevant resources and organizes them into a logical sequence, providing a standardized JSON output for client applications.
How to use MCP Server?
To use the server, you can either run it locally or access the production URL. You can generate MCPs by making GET requests to the /generate_mcp endpoint, specifying the topic and other optional parameters like the number of nodes, language, and category. Asynchronous MCP generation is also supported via the /generate_mcp_async endpoint.
Key features of MCP Server
Generate learning paths for any topic
Find relevant resources using web search and scraping
Organize resources into a logical sequence
Support for multiple languages (focus on Portuguese)
TF-IDF based resource relevance filtering
Strategic quiz distribution
YouTube integration
Asynchronous task system with real-time progress feedback
Enhanced caching system
Optimized web scraping techniques
Adaptive scraping system
Puppeteer instance pool
Use cases of MCP Server
Creating personalized learning experiences
Generating educational content for specific topics
Building educational applications
Automating content curation
Providing structured learning paths for employees or students
FAQ from MCP Server
How do I specify the topic for the MCP?
How do I specify the topic for the MCP?
You specify the topic using the topic parameter in the /generate_mcp endpoint, e.g., /generate_mcp?topic=python.
Can I generate MCPs in different languages?
Can I generate MCPs in different languages?
Yes, you can specify the language using the language parameter, e.g., /generate_mcp?topic=python&language=en for English.
How can I customize the structure of the learning path?
How can I customize the structure of the learning path?
You can customize the number of nodes, minimum/maximum width, and minimum/maximum height of the tree using the num_nodes, min_width, max_width, min_height, and max_height parameters.
What is the purpose of the caching system?
What is the purpose of the caching system?
The caching system improves response times for repeated queries by storing and retrieving previously generated MCPs.
How do I check the status of an asynchronous task?
How do I check the status of an asynchronous task?
You can check the status of an asynchronous task using the /status/{task_id} endpoint, where {task_id} is the ID returned when you initiated the asynchronous task.