Model Context Protocol (MCP)
The property-data backbone powering PriceHubble AI Agents
PriceHubble AI Agents rely on a simple principle: LLMs are only as good as the data you give them.
To guarantee accuracy, safety, and enterprise-grade reliability, we have built and deployed our own Model Context Protocol (MCP) server. It allows AI agents to retrieve property insights directly from our infrastructure. MCPs are the missing infrastructure layer that connects autonomous agents with verified property data, in real time and at scale.
The property-data backbone powering PriceHubble AI Agents
PriceHubble AI Agents rely on a simple principle: LLMs are only as good as the data you give them.
To guarantee accuracy, safety, and enterprise-grade reliability, we have built and deployed our own Model Context Protocol (MCP) server. It allows AI agents to retrieve property insights directly from our infrastructure. MCPs are the missing infrastructure layer that connects autonomous agents with verified property data, in real time and at scale.
What is an MCP?
An MCP is a structured, agent-oriented interface that allows LLM-powered systems to request contextual data safely.
Where an API enables communication between applications, an MCP is built specifically for agentic workflows, providing structured context, granular permissions, deterministic responses, and unified access to curated datasets
APIs were made for applications. MCPs are made for AI Agents.
Launching a Model Context Protocol suite to power more reliable AI property insights
PriceHubble launches an MCP offering dedicated to property data, covering 10 countries and powered by our proprietary data lake and models. Each MCP endpoint exposes a specific domain of the PriceHubble intelligence stack, such as:
Launching a Model Context Protocol suite to power more reliable AI property insights
PriceHubble launches an MCP offering dedicated to property data, covering 10 countries and powered by our proprietary data lake and models. Each MCP endpoint exposes a specific domain of the PriceHubble intelligence stack, such as:
Listings MCP endpoint
Structured access to active listings, attributes, price history, and days-on-market.
Listings MCP endpoint
Structured access to active listings, attributes, price history, and days-on-market.
Transactions MCP endpoint
Curated, deduplicated transaction records and comparables across 10 countries.
Transactions MCP endpoint
Curated, deduplicated transaction records and comparables across 10 countries.
Market Trends MCP endpoint
Local price dynamics, supply indicators, and market evolution metrics.
Market Trends MCP endpoint
Local price dynamics, supply indicators, and market evolution metrics.
Valuation MCP endpoint
Direct access to PriceHubble valuation outputs in a secure, controlled context.
Valuation MCP endpoint
Direct access to PriceHubble valuation outputs in a secure, controlled context.
More MCP endpoints are released by the day as we continue expanding our agentic capabilities.This enables agents to act on real, validated, and localised property insights instead of relying on assumptions or approximations.
More MCP endpoints are released by the day as we continue expanding our agentic capabilities This enables agents to act on real, validated, and localised property insights instead of relying on assumptions or approximations.
How MCPs power our AI Agents
The Companion Agent uses MCP endpoints to deliver personalised insights to property owners on their property (valuation, local trends, relevant listings).
The Copilot Agent (personal assistant) relies on MCP endpoints to navigate transactions, filter comparables, generate market analyses, and surface actionable insights.
This architecture ensures that all agent outputs are grounded in PriceHubble data, consistent across markets, deterministic and fully auditable and ready for large-scale enterprise deployments.
How MCPs power our AI Agents
The Companion Agent uses MCP endpoints to deliver personalised insights to property owners on their property (valuation, local trends, relevant listings).
The Copilot Agent (personal assistant) relies on MCP endpoints to navigate transactions, filter comparables, generate market analyses, and surface actionable insights.
This architecture ensures that all agent outputs are grounded in PriceHubble data, consistent across markets, deterministic and fully auditable and ready for large-scale enterprise deployments.
Why MCPs matter for AI Agents
MCPs give agents a dependable foundation to operate with accuracy, consistency, and trust from the very first interaction.
How MCPs power our AI Agents
The Companion Agent uses MCP endpoints to deliver personalised insights to property owners on their property (valuation, local trends, relevant listings).
The Copilot Agent (personal assistant) relies on MCP endpoints to navigate transactions, filter comparables, generate market analyses, and surface actionable insights.
This architecture ensures that all agent outputs are grounded in PriceHubble data, consistent across markets, deterministic and fully auditable and ready for large-scale enterprise deployments.
Dramatically reduced hallucinations on property data
MCPs provide controlled, factual data. Agents no longer invent answers about market conditions, valuations, or comparisons, they simply query them.
Dramatically reduced hallucinations on property data
MCPs provide controlled, factual data. Agents no longer invent answers about market conditions, valuations, or comparisons, they simply query them.
Enterprise-grade reliability
MCPs align with our security and compliance framework: ISO 27001, ISO 42001-aligned AI governance, privacy-by-design, NIST AI RMF alignment, strong access controls, and full auditability.
Enterprise-grade reliability
MCPs align with our security and compliance framework: ISO 27001, ISO 42001-aligned AI governance, privacy-by-design, NIST AI RMF alignment, strong access controls, and full auditability.
Production-ready at scale
Built on our enterprise-grade infrastructure, MCPs are designed to support real workloads from banks, brokers, investors, and large real estate operators.
Production-ready at scale
Built on our enterprise-grade infrastructure, MCPs are designed to support real workloads from banks, brokers, investors, and large real estate operators.
One protocol for all agentic use cases
Agents can seamlessly pull data across domains such as listings, comparables, valuations, and market trends without requiring custom integrations.
One protocol for all agentic use cases
Agents can seamlessly pull data across domains such as listings, comparables, valuations, and market trends without requiring custom integrations.
From Q2 2026, our MCPs will be available to external customers through an early access beta, allowing you to plug directly into the same property data infrastructure we use internally. If you’d like to explore how MCP can support your AI strategy or begin integrating it into your agentic workflows, please reach out to our team.
Dramatically reduced hallucinations on property data
MCPs provide controlled, factual data. Agents no longer invent answers about market conditions, valuations, or comparisons, they simply query them.
Enterprise-grade reliability
MCPs align with our security and compliance framework: ISO 27001, ISO 42001-aligned AI governance, privacy-by-design, NIST AI RMF alignment, strong access controls, and full auditability.
Production-ready at scale
Built on our enterprise-grade infrastructure, MCPs are designed to support real workloads from banks, brokers, investors, and large real estate operators.
One protocol for all agentic use cases
Agents can seamlessly pull data across domains such as listings, comparables, valuations, and market trends without requiring custom integrations.
Become an early adopter
Become an early adopter
Let’s build the next generation of property-intelligence agents together.
Request a demo
Request a demo
We will get back to you quickly.
We look forward to speaking with you.
Request a demo
We will get back to you quickly.
We look forward to speaking with you.
Thank you!
We will get back to you within 24 business hours.
Thank you!
We will get back to you within 24 business hours.