In the first post of this series, I introduced the vision for our Multi-Connector Platform (MCP) Hub—the central nervous system for AI in financial services. Now, I want to move from the "why" to the "how." How, exactly, does the Hub tame the chaos of AI adoption and give our customers the control they need to operate with confidence?
The answer lies in two key concepts: Orchestration and Governance.
At the core of the Hub is a Tool Registry. Think of it as an inventory system for all AI capabilities available within the organization. Before any end-user can leverage an AI assistant to, say, analyze an earnings call transcript or perform a KYC check, that tool must be registered in the Hub by an administrator.
This simple act of registration is incredibly powerful. It means that for the first time, administrators have a complete and real-time picture of the AI tools in use across their enterprise. But it goes further than just a list. As one of our key user stories for the Admin persona outlines:
"As an Admin, I want to register a new internal or external tool with the Hub, defining its connection details, authentication methods, and associated metadata, so that it can be managed and assigned via access policies."
This allows the Hub to become the central orchestrator, managing how and when these tools are called upon, ensuring that requests are properly authenticated, and logging every action for a complete audit trail.
Once the tools are registered, the next step is controlling who can use them. The financial services industry is built on a foundation of roles and responsibilities, and AI usage must reflect that. You wouldn't give a junior analyst access to the same sensitive client data as a senior portfolio manager, and the same principle must apply to the AI tools they use.
The MCP Hub enables this through a robust, policy-based access control engine. Administrators can create fine-grained policies that govern tool usage based on a user's role, their team, the type of data they are trying to access, and even the context of their request.
We are aiming for a success metric of 100% of tools being registered with access policies and audit logging enabled. This isn't just a target; it's a commitment to providing the watertight governance that our customers require. Through a dedicated Admin Dashboard, our customers will be able to manage these policies, monitor usage patterns in real-time, and investigate any anomalies, turning the "black box" of AI usage into a transparent, auditable, and fully governed process.
By combining centralized orchestration with granular governance, the MCP Hub transforms AI from a source of potential chaos into a well-managed, strategic asset. In the next post, I'll dive into the specific security architecture that underpins this entire system, because in finance, even the best governance is meaningless without enterprise-grade security.