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Model Context Protocol

MCP Server

Connect AI agents directly to the intelligence layer. Query loans, resolve entities, and traverse the capital graph from Claude, GPT, or any MCP-compatible client.

Overview

What Is MCP

The Model Context Protocol is an open standard that lets AI agents call structured tools and read typed resources from external systems. Instead of pasting data into prompts or building custom integrations, MCP gives your agent direct, authenticated access to the full Real Intelligence data layer.

Structured Tools
Search loans, resolve entities, traverse the capital graph, and pull decision-ready signals. The agent picks the right tool for the query.
Typed Resources
Schema definitions and field taxonomies the agent reads to understand the data model before querying. No hallucinated field names.
Authenticated Access
API-key scoped to your subscription tier. The server enforces the same access controls as the REST API. No data leakage across tenants.
Setup

Installation

Add the Real Intelligence MCP server to your client configuration. The example below shows Claude Desktop, but any MCP-compatible client works the same way.

claude_desktop_config.json
{
  "mcpServers": {
    "real-intelligence": {
      "command": "npx",
      "args": ["-y", "..."],
      "env": {
        "REAL_INTELLIGENCE_API_KEY": "ri_demo_key"
      }
    }
  }
}

// Package details provided with MCP access.

Replace ri_demo_key with the key issued in your onboarding package. The server authenticates on every call and scopes responses to your subscription tier.

Tools

Available Tools

Tools covering the full intelligence surface: loan search, entity resolution, capital graph traversal, and signal retrieval. The agent selects the right tool based on the user's natural-language query.

Loan SearchTool
Search and filter loan records across the full dataset. Accepts geographic, lender, balance, and maturity parameters with paginated results.
Example usage
"Find loans in New York above $15M maturing in the next 18 months"
Loan DetailTool
Retrieve the complete record for a single loan, including collateral context, debt sizing, and lender metadata.
Example usage
"Pull the full record for this loan"
Entity LookupTool
Look up resolved entities by name, type, or resolution confidence. Returns relationship metadata and ownership context.
Example usage
"Find all resolved sponsor entities matching this name"
Ownership ChainTool
Walk the full ownership chain for an entity — from borrower through operating company to ultimate beneficial owner.
Example usage
"Who is the ultimate beneficial owner behind this entity?"
Graph QueryTool
Traverse the capital graph from any node. Returns connected entities, relationship paths, and concentration metrics at configurable depth.
Example usage
"Map the capital chain from this lender's office portfolio to upstream allocators"
Signal FeedTool
Retrieve decision-ready flags for rate pressure, concentration risk, maturity timing, and other mandate-level filters.
Example usage
"Show high-severity signals in this market"
Resources

Available Resources

MCP resources expose read-only schema and taxonomy data that the agent uses to understand the data model. The client reads these before making tool calls, so field names and types are always accurate.

Schema definitions and field taxonomy available as MCP resources. The agent reads these automatically to understand the data model before querying — ensuring accurate field names, types, and query structure with no hallucination. Full resource documentation is provided with MCP access.

In Practice

Example Conversations

The MCP server turns natural-language questions into structured queries against the intelligence layer. Here is what that looks like in practice.

User prompt
“Show me loans in this market that are approaching maturity under pressure.”
What happens
The MCP server queries the loan dataset with the relevant filters and returns matching records with debt sizing, lender, and collateral context — structured for immediate analysis.
User prompt
“Who is the ultimate beneficial owner behind this borrower?”
What happens
The server chains multiple tools together — resolving the borrower entity, then walking the ownership chain through intermediate entities to the UBO, returning the full path.
User prompt
“Map the capital relationships for this lender's portfolio in this market.”
What happens
The server identifies the relevant positions, then traverses the capital graph to return connected entities, relationship paths, and concentration metrics.
Pricing

MCP Access

The MCP server is an add-on to any Real Intelligence subscription. Same data, same access controls, delivered through the protocol your agents already speak.

MCP Add-On

Available as an add-on to any data subscription. Contact for pricing.

Includes authenticated server, full tool suite, typed resources, and usage within your API rate limits. No per-seat charges. Connect as many agents as your workflow requires.

Annual license. Billed alongside your base subscription.

Connect your agents

Structured CRE intelligence, native to your AI stack.

Request MCP access to receive server credentials and onboarding details.

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