Model Context Protocol

Model Context Protocol

The Model Context Protocol (MCP) is a standard developed by Anthropic that enables AI models to use tools by defining a structured format for tool descriptions, calls, and responses.

It defines a standardized way for LLMs to discover, call, and use tools, often hosted on local or remote servers, via HTTP + JSON RPC2.0.

Function calling is like giving LLM a calculator app.

MCP is like giving LLM an App Store — which can browse, discover, and use any available tool on its own.

When to use Function Calling vs Model Context Protocol (MCP) ?

Function Calling to be used when:

  • We require simple tools
  • We control the whole application stack
  • We’re using cloud models like ChatGPT or Gemini
  • We want tight integration in our application logic

MCP to be used when:

  • We’re building agentic systems
  • We want tools to be modular, reusable, discoverable
  • We want local LLMs (like Ollama, Gemma, Mistral) to use external data
  • We want scaling to multiple tools or toolchains

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