The verified location layer for AI
Everyone in real estate now uses the same AI, and that AI is confidently wrong about the questions that decide a transaction. The Local Logic MCP connects any AI application to our verifiable location data over the Model Context Protocol, so it answers from measurement.
Grounded answers you can stand behind
Answer from measurement, not memory
The MCP hands your AI the verified answer at the moment of the question. It exposes our location data as read-only tools the model calls mid-response, so it reads real numbers instead of reaching for them. Same model, same question, now grounded, with an honest “no data” when coverage runs out.
20+ tools, one connection
Ground answers on calibrated location scores, neighborhood profiles and measures, similar neighborhoods and affordable alternatives, points of interest, demographics, schools, and US market statistics. Commute routing and climate risk are rolling out next.
Proven in our testing
- Up to 2.3x more verified facts per answer.
- Up to 97.8% claim accuracy; the biggest jump was a cheap model gaining 17 points, from 78 to 94%.
- Live web search is not a substitute: a dedicated retrieval product reached only 82%, below every grounded model.
Built for trust, and already in production
Read-only by design, it never trains on your queries, and your Local Logic entitlements apply. Measured attributes only: no crime data, no protected-class fields, no steering. Infinityy is already using the Local Logic MCP to power more accurate answers in its AI chatbot. It works with the tools teams already use, including Claude, Cursor, VS Code, Codex CLI, and the OpenAI and Anthropic APIs.
Frequently asked questions
What is the Local Logic MCP?
It is a hosted server that gives any AI application access to Local Logic verified location data as read-only, callable tools over the open Model Context Protocol. The model looks up measured facts about a place, such as walkability, amenities, schools, demographics, and market data, and answers from that data instead of guessing.
Do I need to install or host anything?
No. It is a hosted remote server. You connect your MCP-compatible client to one URL with your MCP key, with nothing to install or run.
Which AI clients and models work with it?
Any MCP-compatible client, including Claude, Cursor, VS Code, and Codex CLI, plus the OpenAI Responses API and the Anthropic Messages API. Coverage is the US and Canada.
What data can the MCP return?
Calibrated location scores, neighborhood profiles and measures, similar neighborhoods and affordable alternatives, points of interest, demographics, schools, and US market statistics. Commute routing and climate risk are rolling out next.
How is this different from a generic AI answer or web search?
A generic model answers a location question from memory and cannot tell you which parts are real. Grounded in Local Logic data it answers from measurement. In our testing a dedicated web-retrieval product reached only 82% accuracy on the proprietary categories, below every grounded model.
How much does grounding improve accuracy?
In an evaluation of 7 models on 490 questions across 46 neighborhoods, grounding delivered up to 2.3x more verified facts per answer, lifted claim accuracy up to 97%, and roughly halved answers with serious errors, from 32 to 17% materially wrong on average.
Does it train on our data or change anything?
No. The server is read-only and cannot create, modify, or delete anything. It does not train on your queries, and access to tools and regions mirrors your Local Logic entitlements. It uses measured attributes only, with no crime data and no protected-class fields.
How do I get access?
Contact us to enable the MCP on your account and receive your MCP key, then follow the technical documentation to connect your client in minutes.
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