Introduction
Get started with the Model Context Protocol (MCP)
MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.
Why MCP?
MCP helps you build agents and complex workflows on top of LLMs. LLMs frequently need to integrate with data and tools, and MCP provides:
- A growing list of pre-built integrations that your LLM can directly plug into
- The flexibility to switch between LLM providers and vendors
- Best practices for securing your data within your infrastructure
General architecture
At its core, MCP follows a client-server architecture where a host application can connect to multiple servers:
- MCP Hosts: Programs like Claude Desktop, IDEs, or AI tools that want to access data through MCP
- MCP Clients: Protocol clients that maintain 1:1 connections with servers
- MCP Servers: Lightweight programs that each expose specific capabilities through the standardized Model Context Protocol
- Local Data Sources: Your computer’s files, databases, and services that MCP servers can securely access
- Remote Services: External systems available over the internet (e.g., through APIs) that MCP servers can connect to
Get started
Choose the path that best fits your needs:
Quickstart
Build and connect to your first MCP server
Examples
Check out our gallery of official MCP servers and implementations
Clients
View the list of clients that support MCP integrations
Tutorials
Building a MCP client
Learn how to build your first MCP client
Building MCP with LLMs
Learn how to use LLMs like Claude to speed up your MCP development
Debugging Guide
Learn how to effectively debug MCP servers and integrations
MCP Inspector
Test and inspect your MCP servers with our interactive debugging tool
Explore MCP
Dive deeper into MCP’s core concepts and capabilities:
Core architecture
Understand how MCP connects clients, servers, and LLMs
Resources
Expose data and content from your servers to LLMs
Prompts
Create reusable prompt templates and workflows
Tools
Enable LLMs to perform actions through your server
Sampling
Let your servers request completions from LLMs
Transports
Learn about MCP’s communication mechanism
Contributing
Want to contribute? Check out @modelcontextprotocol on GitHub to join our growing community of developers building with MCP.
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