Connecting Corporate AI with Live Financial Data: N3XT Unveils MCP

N3XT, a blockchain-based bank specializing in B2B payments, has launched its Model Context Protocol (MCP) implementation designed to bridge corporate AI environments directly to live banking data. The product went live on July 28, 2026, enabling secure and governed access for AI agents operating within company infrastructure.

Key Features of N3XT MCP

  • Allows AI agents to query balances, draft payments, generate reports, and trigger workflows
  • Preserves existing security controls like maker-checker approvals
  • Keeps data processing entirely within corporate firewalls
  • Supports both read access for analysis and governed write capabilities for automated actions

How It Works

Rather than requiring manual data exports or switching between systems, N3XT MCP provides a standardized interface where AI assistants can initiate banking operations through natural language commands. For example, a treasury analyst could instruct an agent to “draft a payment to vendor X for invoice Y,” which would follow the same approval chain as if done manually.

“We’re standardizing how AI agents access live bank data and enabling clients to work within trusted environments,” said Aurélien Bonnel, founder and CTO of N3XT. The MCP is built on an open standard that defines structured, permissioned interactions between AI systems and external services.

Market Implications

This launch signals a growing trend in corporate banking where vendors are racing to make their data accessible via APIs for integration with large language models. While many offer similar connectivity, N3XT’s approach stands out by providing a dedicated agentic protocol layer rather than just API enhancements.

As AI adoption accelerates across industries, solutions like MCP address the need for secure and governed access to financial data while keeping sensitive operations within corporate control. However, clients should carefully evaluate how these automated workflows impact operational risk and ensure compliance with evolving regulations around AI in finance.