MCP Server Sample

by antonioscapellato

This repository provides an educational implementation of a Model Context Protocol (MCP) server. It demonstrates how to build a functional MCP server that can integrate with various LLM clients.

View on GitHub

Last updated: N/A

What is MCP Server Sample?

This is an implementation of a Model Context Protocol (MCP) server. MCP standardizes how applications provide context to LLMs, acting as a standardized way to connect AI models to different data sources and tools.

How to use MCP Server Sample?

To use this server, you need Python 3.10 or higher, MCP SDK 1.2.0 or higher, and the uv package manager. You can install the server using uv add "mcp[cli]" or pip install "mcp[cli]". A quickstart example is provided to create a simple server with a calculator tool and a dynamic greeting resource.

Key features of MCP Server Sample

Standardized context for LLMs
Growing list of pre-built integrations
Flexibility to switch between LLM providers
Best practices for securing data
Supports Resources, Tools, and Prompts

Use cases of MCP Server Sample

Integrating LLMs with local data sources
Connecting LLMs to remote APIs
Providing LLMs with pre-written prompts
Building AI tools with standardized context
Enabling secure data access for LLMs

FAQ from MCP Server Sample

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs.

What are the key benefits of MCP?

Key benefits include pre-built integrations, flexibility to switch LLM providers, and best practices for data security.

What are the core MCP concepts?

Core concepts include Resources (file-like data), Tools (functions), and Prompts (pre-written templates).

What are MCP Hosts?

Programs like Claude Desktop, IDEs, or AI tools that want to access data through MCP

What are MCP Servers?

Lightweight programs that expose specific capabilities through the standardized Model Context Protocol