MCP Security Overview

The Model Context Protocol implements a robust security framework based on industry-standard OAuth 2.1, ensuring that your AI applications can safely interact with external resources while maintaining strict access controls. This security model protects both your organization's data and the AI systems that access it.

Security Architecture

MCP's security model is built on three key components: the authorization server, resource server, and client. The authorization server manages access permissions and issues secure tokens. The resource server protects your valuable data and tools. The client component ensures secure communication between these elements.

Access Control

MCP provides granular control over what resources AI systems can access. Through OAuth 2.1, you can define specific permissions for different AI applications, ensuring they only access the data and tools they need. This fine-grained access control helps maintain the principle of least privilege across your organization.

Security Features

The protocol includes several key security features:

• Secure token-based authentication
• Short-lived access tokens to minimize risk
• Protected resource discovery
• Automatic client registration
• HTTPS-only communication

Implementation Security

When implementing MCP, security is built-in at every level. All communication is encrypted using HTTPS, and the protocol includes measures to prevent common security threats like token theft and unauthorized access. The system automatically handles token rotation and secure storage, reducing the risk of security breaches.

Best Practices

MCP encourages following security best practices such as:

• Regular token rotation
• Secure client registration
• Protected resource metadata
• Proper error handling
• Secure redirect URI validation

By implementing MCP's security model, organizations can confidently integrate AI systems with their existing infrastructure while maintaining strong security controls and protecting sensitive data.