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Implementation

MCP Server

Definition

An MCP (Model Context Protocol) server is a program that exposes data, tools, and context to AI applications through Anthropic's open standard, enabling LLMs to interact with external systems.

Why It Matters

MCP standardizes how AI applications connect to external systems - databases, APIs, file systems, and more. Instead of building custom integrations for each AI tool, you build one MCP server that works everywhere. This “USB-C for AI” approach simplifies building AI applications that interact with the real world.

How It Works

AI Application (Host) ↔ MCP Client ↔ MCP Server ↔ Your Data/Tools

MCP servers expose:

  • Resources: Data the AI can read (files, database entries)
  • Tools: Functions the AI can call (search, create, update)
  • Prompts: Template prompts for common operations

Building an MCP Server

# Simple MCP server example
from mcp.server import Server
server = Server("my-server")

@server.tool()
def search_database(query: str) -> str:
    # Your implementation
    return results

SDKs available for Python, TypeScript, and other languages.

Use Cases

Database access for RAG, file system operations, API integrations (Slack, GitHub, etc.), custom business logic, and connecting AI to internal tools.

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