In March 2026, Intelligo launched an MCP server for investment due diligence. It checks backgrounds on people and entities — who is this person, what is their reputational history, do they pass compliance screening. It generates audit-ready records and embeds background check triggers directly into autonomous investment workflows.

Around the same time, PriceHubble’s MCP server made property-level data queryable — market comps, valuation models, location analytics, pulled directly into the AI workflow without leaving to a separate platform.

Two MCP servers, two distinct layers of the same workflow. Neither competes with the other. Together they cover two-thirds of a real estate investment due diligence workflow. The third layer — document analysis — is not yet covered by any MCP server in the ecosystem.

This is how professional workflows get assembled in the MCP era: not as monolithic platforms, but as stacked, complementary layers, each handling a distinct domain of the workflow, all composable in the same interface.

The pattern makes sense when you consider what due diligence actually requires. Before making an investment, a real estate fund needs to know: who is this counterparty (people layer), what does the market say about this asset (data layer), and what do the actual documents say (document layer). These are three fundamentally different information problems requiring three different data sources and three different types of analysis. No single tool has ever done all three well. The MCP model doesn’t try to collapse them — it makes them composable.

For each layer, the right builder is the one who understands the specific problem deeply. Background check specialists built the people layer because entity resolution and compliance data are their core competency. Property data platforms built the data layer because market analytics is their core competency. The document layer will be built by someone who understands leases, rent rolls, title reports, and environmental assessments deeply enough to extract what actually matters — the clauses that affect value, the terms that create liability, the gaps that require follow-up.

The interesting thing about the layer stack model is that it solves the enterprise adoption problem that monolithic platforms have always faced. Asking a firm to replace their entire due diligence workflow is a massive ask. Asking them to add a specialized capability to the workflow they already run in Claude Desktop is a minimal ask. Each layer gets evaluated on its own merits. Each layer creates its own switching cost. And each layer, once embedded, makes the overall stack more valuable and more defensible.

The document layer of the due diligence stack is the last unclaimed piece. Two of three layers exist. The workflow is assembling itself around the gap.

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