How MCP Changes Everything for AI Task Delegation

Before MCP, AI agents were isolated. They could process text and generate responses, but they couldn't reach out to external services in a standardized way. Every integration was custom and fragile.

The Model Context Protocol changes that. It gives AI agents a universal way to discover and use external tools. For Final Leg, this means any MCP-compatible AI client can post tasks, check statuses, and manage the entire task lifecycle without any custom integration work.

What MCP actually is

MCP is a protocol — think of it like HTTP for AI tool use. It defines a standard way for AI clients (like Claude Desktop, Cursor, or Claude Code) to connect to external servers that expose tools. When you connect Claude to Final Leg's MCP server, Claude gains new capabilities: posting a task, checking task status, listing tasks, verifying completion, and canceling a task.

You don't need to learn a new interface or visit a different website — you just talk to your AI naturally. 'Post a task on Final Leg to call my insurance company and dispute this claim. Budget $35.' The AI handles the rest.

Beyond MCP: OpenAPI for everyone

Not every AI platform supports MCP yet. That's why Final Leg also exposes a full REST API with an OpenAPI specification. ChatGPT connects through OpenAPI Actions. Google AI Studio uses function declarations. Any platform that can make HTTP requests can integrate with Final Leg.

The result: whether you use Claude, ChatGPT, Cursor, OpenClaw, or something we haven't heard of yet — your AI can delegate tasks to human workers on Final Leg.

Ready to bridge the last mile?