Viraj Sharma
Im a passionate programmer interested in Python, AI, and computer vision. I am studying in class 8, presidium school indirapuram delhi. As an active python community member, I enjoy learning from experienced developers and sharing insights. I have worked with OpenCV, TensorFlow, and Streamlit, exploring computer vision, automation, and AI. I love solving problems, building projects, and understanding how technology impacts the real world. I actively participate in tech meetups, hackathons, and open-source communities, gaining hands-on experience with deep learning, NLP, and data science. I've also given lightning talks at PyDelhi, pyconfererence bangalore, discussing Python frameworks and AI applications. Always eager to connect, collaborate, and learn
Session
The Model Context Protocol (MCP) is an emerging standard that enables structured data provisioning for LLMs and AI agents. However, the current data discovery mechanism in MCP is static. This limits the AI’s ability to dynamically assess the utility, relevance, and efficiency of data tool calls in real time. Here I present an enhancement to MCP "tool discovery" that introduces dynamic data descriptions, allowing LLM to be better informed.