X-Agent, an AI Agent Onchain OS, released a new white paper on Sept. 21 detailing its product architecture, MCP ecosystem, business model, and the use cases planned for $XAGT.
The white paper says the next stage of the AI industry is not just about generating text, images, or code. It frames the next step as giving agents the ability to understand user intent, call tools, execute tasks, and complete transactions.
Natural-language agent creation
Under the idea of 「Speak to Build, Share to Connect」, X-Agent said users can create AI agents through natural language without writing code. The agents are designed with context, memory, skills, API connectivity, and wallet connection capabilities.
Business model and MCP integration
On the business side, X-Agent said it wants to connect the full chain of agent creation, MCP capability access, distribution, payments, and monetization. Developers can package APIs, data, and professional services into MCP capabilities, then generate revenue through per-call charges, subscriptions, or trading commissions.
Planned uses for $XAGT
According to the white paper, $XAGT is intended for computing costs in secure runtime environments, LLM and API calls, agent transaction settlement, payments for MCP services, purchases of Premium Agent templates, and developer deployment.
The project said future use cases may expand to service staking, multi-agent settlement, and ecosystem governance.
Disclosed metrics and roadmap
According to the project, X-Agent now has more than 1 million registered users, has completed more than 1.1 million autonomous tasks, and has recorded more than 84 billion LLM tokens consumed.
Looking ahead, the project said it plans to advance Super-Agent, an enterprise sandbox, a decentralized Agent Store, and a multi-agent collaboration system.
Through the white paper, X-Agent said it wants to clarify its long-term direction: letting anyone create an agent through language, while giving agents the ability to execute, distribute, pay, and sustain commercialization.