A new lightweight framework called Tiny Agents lets developers create AI agents with minimal code. The tool leverages the Model Context Protocol (MCP) to connect agents to external tools and data sources, enabling tasks like web searches, file operations, and API calls. The entire agent logic fits in 50 lines of Python, making it accessible for quick prototyping and education.
The approach strips away boilerplate, focusing on core agent loops: parsing user intent, selecting tools, and executing actions. Tiny Agents is open-source and designed to run with any LLM that supports function calling. Developers can extend it with custom tools by adding simple JSON schemas.
"We wanted to show that agent infrastructure doesn't need to be complex," said the creator. "With MCP and modern LLMs, the hardest part is just defining what your agent can do."