MCP Introduction

What is MCP?

Model Context Protocol (MCP) is a standardized way for AI agents to interact with applications and services. @warpy-auth-sdk/core implements MCP to enable AI agents to authenticate on behalf of users with scoped, time-limited access.

Why MCP for Authentication?

Traditional authentication is designed for human users, but AI agents need different capabilities:

• Delegated Access: Agents act on behalf of users
• Scoped Permissions: Limited access to specific resources
• Time-Limited: Short-lived tokens for security
• Audit Trail: Track agent actions and access

Use Cases

MCP authentication enables AI agents to:

• Debug Issues: Agents can access user data to diagnose problems
• Automate Tasks: Perform routine operations on behalf of users
• Data Analysis: Analyze user data with appropriate permissions
• Support: Help users with account-related issues

Security Model

MCP authentication includes several security features:

• Short-lived Tokens: Default 15-minute expiration
• Scope-based Access: Agents can only access permitted resources
• Token Revocation: Immediate invalidation when needed
• Audit Logging: Track all agent actions

Basic Example

Here's a simple example of MCP agent authentication:

// AI agent requests authentication
const response = await fetch('/api/mcp', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    tool: 'agent_login',
    args: {
      userId: 'user-123',
      scopes: ['debug', 'read'],
      agentId: 'claude-assistant',
      expiresIn: '15m'
    }
  })
});

const { token } = await response.json();

// Use token for authenticated requests
const userData = await fetch('/api/user/profile', {
  headers: {
    'Authorization': `Bearer ${token}`
  }
});

Next Steps

Learn more about MCP implementation:

• Agent Authentication - How agents authenticate
• Tools Reference - Available MCP tools
• AI SDK Integration - Using with Vercel AI SDK
• Security Model - Security considerations