Function calling and MCP solve overlapping problems, and the difference genuinely matters if you’re deciding how to connect a model to your own tools.
Function calling is a direct, provider-specific feature: you define a function’s name, parameters, and description, and the model decides when to call it. Simple, no extra infrastructure, but it locks you into building and maintaining that integration for each provider separately.
MCP is a standard protocol sitting on top of the same basic idea: any MCP-compatible client can use any MCP-compatible server. Build one server and every compatible client can use it, no per-provider integration required.
A quick, single-purpose integration for one specific product: function calling is simpler and faster to ship. A tool meant to work across multiple AI clients, or one you’re publishing for others to use: MCP’s standardization is worth the extra setup. Read the full specification at modelcontextprotocol.io before deciding.
