Beginner LevelAI, LLMs, Embeddings & MCP
What is the Model Context Protocol (MCP) and how does it connect LLMs to external tools?
❓ Interview Prompt: Explain the open Model Context Protocol architecture, host-client-server roles, and JSON-RPC communication.
Model Context Protocol (MCP) is an open standard developed to standardize how Large Language Model (LLM) applications connect to external tools, local databases, and enterprise data sources.
Core Architecture:
1
Host (Client Application): An AI application (e.g. Claude Desktop, Cursor, or a custom LLM host) that controls the context window and model interactions.
2
MCP Server: Lightweight server exposing specialized capabilities (e.g. filesystem tools, GitHub APIs, Postgres database querying).
3
Protocol Layer: Standardized JSON-RPC 2.0 messaging over Stdio or Server-Sent Events (SSE).
Problem Solved:
Replaces custom N×M brittle API integrations with a universal 1×N protocol standard. Any MCP server works automatically with any MCP-compliant client.
Code Implementation Example
json
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "query_database",
"arguments": {
"sql": "SELECT id, email FROM users WHERE status = 'active' LIMIT 5"
}
}
}💡Standardized JSON-RPC tool call payload in Model Context Protocol.
🎯 Interview Key Takeaway
MCP standardizes tool and data integration for LLMs via JSON-RPC 2.0, eliminating custom integration glue code.
#MCP#Architecture#Protocol#JSON-RPC#Beginner
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