How to Build Your First MCP Server: Full Guide for Developers
Blog post from Helicone
Anthropic's Model Context Protocol (MCP) is a versatile standard allowing AI applications to seamlessly interact with external tools, APIs, and services using natural language, thereby expanding the capabilities of AI agents beyond basic chat functionalities. The guide provides a comprehensive walkthrough on integrating pre-built MCPs like Figma into AI applications, constructing a custom MCP server for tailored needs, and enhancing observability using Helicone for efficient monitoring and debugging. By establishing a custom MCP server, developers can gain full control over how their AI interacts with external APIs, exemplified by creating a Weather MCP server that fetches live temperature data. The integration of Helicone allows for robust tracking of LLM usage across various providers, offering insights into costs, performance metrics, and usage patterns. The use of MCP facilitates a standardized interface for AI applications to engage with external systems, and with growing support from major tech entities, it is poised to significantly enhance LLM capabilities.