YT - MCP vs API: Simplifying AI Agent Integration with External Data

June 21, 2025 · Scrib

LLM needs to communicate with external data sources to be truly useful
Anthropic came up with the Model Context Protocol - “standardizes how applications provide context to LLMs”
MCP is like a USB for your AI applications. USB can be used regardless of manufacturers.
Each MCP Host Client opens a JSON RPC 2.0 session using the MCP protocol, and that connects to MCP servers (e.g. database, email storage)
MCP does … 1) provides a standardized way to retrieve contextual data to AI Agents 2) enables usage of tools(web search, API call, calculation, db lookup) by AI Agents
MCP server primitives … 1) tools: discrete actions or functions the AI can call 2) resources: read-only data items the server can provide e.g. db schema, file content 3) prompt templates
AI agents can “query an MCP server to discover what primitives are available and invoke those capabilities in a uniform way”
RESTful API communicates of HTTP using methods such as get, post, put, delete
MCP supports dynamic self discovery - client can ask “what can you do?”
MCP servers is also a wrapper around an API. Many of the tools are APIs. In this case MCP is an AI friendly interface of APIs.
MCP systems are deployed in file systems, Docker, Spotify, Google Maps etc.