Enterprise software company nCino released Mortgage MCP in early August 2026, a Model Context Protocol integration that lets mortgage lenders connect AI agents directly to loan origination and servicing data. The North Carolina-based company built the tool on the open MCP standard, giving lenders a structured way to plug autonomous AI agents into workflows spanning the full mortgage lifecycle, from origination through closing, rather than relying on isolated point solutions.
The launch lands as enterprise buyers are rapidly prioritizing agentic AI. Research firm Futurum Group's 1H 2026 Enterprise Software Decision Maker Survey, which polled 830 global IT decision-makers, found that 86.6 percent now rank autonomous agents and agentic AI as a high-priority underlying technology, a figure consistent with the prior survey wave. Analysts say that consistency across two consecutive survey periods signals durable demand for agentic tools rather than a short-lived trend.
Integration capability, not raw AI power, is emerging as the deciding factor in enterprise buying decisions. The same survey found 55.2 percent of buyers cited improved integration capabilities as a top driver of AI budget confidence, down slightly from 72.4 percent in the prior wave but still the leading factor cited. By building Mortgage MCP on an open standard rather than a proprietary connector, nCino is betting that lenders juggling loan origination systems, core banking platforms and third-party data providers will pay for AI tools that plug into existing infrastructure with minimal friction.
The broader enterprise software market backdrop supports the strategy. Futurum's base-case forecast projects the market growing from 379 billion dollars in 2025 to 762 billion dollars by 2031, and analysts note that vertical software vendors with deep domain data tend to capture outsized value as buyers move from AI experimentation into production deployment.
Source: Futurum Group -- https://futurumgroup.com/insights/ncinos-mortgage-mcp-a-major-shift-for-lenders-in-ai-integration/