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Discover how to implement a small and powerful AI agent using Model Context Protocol (MCP) in just 50 lines of code. The post covers the integration of MCP with large language models (LLMs) to create agentic AI, featuring JavaScript and TypeScript components with Hugging Face's SDKs and tools. It also demonstrates the use of MCP servers and shows how tools can be utilized within an LLM inference client.

Tiny Agents: a MCP-powered agent in 50 lines of code

The foundation for this: tool calling native suport in LLMs.

Implementing a MCP client on top of InferenceClient

I ran through the demo. Quite impressive. I’ll be implementing something similar in the next few months for a project.
Really looking forward to some wider industry adoption and perhaps IETF showing up and making a standard.

This is actually cool. Implemented
this in our current project
Used ollama - llama 3.1 8b model
Created a wrapper python server to make the model use the available tools
Created own MCP servers using node.
With this In our MNC I made the logs rest API as an MCP server and connected it to the copilot now copilot is analysing logs
The results are quite impressive!