Learn Tune AI

• 

  Streamlit web application

• 

Inspiration

Students sometimes find it difficult to remember concepts by reading notes repeatedly. Music and catchy lyrics can make learning more interesting and easier to remember. We wanted to build an AI tool that connects studying with music.

What it does

Allows students to enter a topic or upload study notes in PDF format. Uses AI to generate educational song lyrics from the topic or notes. Provides audio playback of singing samples and options to download lyrics and available audio.

How we built it

Used Python and Streamlit to create the application interface. Integrated Google's Gemini API to generate educational lyrics. Used the Model Context Protocol (MCP) to expose the lyric-generation tool and PyPDF to extract text from PDFs.

Challenges we ran into

Setting up the MCP server and handling communication between the application and the AI tool. Extracting readable text from uploaded PDF files. Finding a free way to generate singing audio and understanding the limitations of integrating external music tools.

Accomplishments that we're proud of

Built a working application that generates educational lyrics from topics and PDF notes. Successfully connected the lyric-generation tool to Gemini through our local MCP server. Added PDF text extraction, lyric downloads, and audio playback for singing samples.

What we learned

Learned how to integrate an AI API into a Python application. Understood how MCP tools work and how to connect them to an application. Gained practical experience with PDF processing, testing, and building an AI-based project.

What's next for Learn Tune AI

Integrate automatic singing generation so new lyrics can become complete songs. Improve the application with better audio playback and song download features. Explore a real Alexa+ integration and make the learning experience more conversational.

Built With

• google-gemini-api
• model-context-protocol-(mcp)
• pypdf
• python
• streamlit