---
title: Introduction
description: 'Get started with the Model Context Protocol (MCP)'
---
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.
## Quickstart Guides
Choose the path that best fits your needs:
The fastest way to see MCP in action - connect example servers to Claude in minutes
Create a simple MCP server in TypeScript to understand the basics
Create a simple MCP server in Python to understand the basics
Add MCP support to your TypeScript/JavaScript LLM application
Add MCP support to your Python LLM application
## Explore MCP
Dive deeper into MCP's core concepts and capabilities:
Understand how MCP connects clients, servers, and LLMs
Expose data and content from your servers to LLMs
Create reusable prompt templates and workflows
Enable LLMs to perform actions through your server
Let your servers request completions from LLMs
Learn about MCP's communication mechanisms
## Example Use Cases
See what you can build with MCP:
Connect your documentation, wikis, and internal knowledge bases to LLMs
Query databases and analyze results with natural language
Build AI-powered development tools with access to local files and git
Securely connect enterprise tools and data to AI interfaces
## Security and Best Practices
MCP is designed with security in mind, but requires careful implementation:
Learn about MCP's security model, best practices, and implementation guidelines
Want to contribute? Check out our [GitHub repository](https://github.com/modelcontextprotocol) or join our growing community of developers building with MCP.