MCPTRINV Server

Overview

(also referred to as MCPTRINV) is a Model Context Protocol server that augments AI assistants such as Claude and Gemini with geospatial lookup capabilities derived from the French cadastral platform TRINV. The server exposes two primary tools: one for searching municipalities by name fragment and another for retrieving parcel (cadastral plot) data within a specified commune that meets a given area threshold. By bridging the gap between conversational AI and authoritative land‑registry data, MCPTRINV empowers developers to build applications that require precise geographic information without having to handle the intricacies of web scraping or API key management.

The core value proposition lies in its ability to transform natural language queries into structured cadastral data. For example, a user might ask an AI assistant to “find parcels in the town of Saint‑Pierre that are larger than 2 ha.” MCPTRINV translates this request into a sequence of TRINV searches, returning a list of parcel identifiers, coordinates, and surface measurements. Developers can then use this data to feed downstream processes—such as mapping visualizations, property valuation tools, or compliance checks—directly into their workflows.

Key features of the server include:

• Municipality search (): Accepts partial or full names and returns matching communes with their official codes.
• Parcel search (): Filters parcels within a chosen commune by surface area, providing detailed cadastral information.
• MCP integration: Seamlessly registers as a server in Claude or Gemini, allowing assistants to invoke the tools via natural language commands.
• Node.js implementation: Built on a lightweight Node environment, making it easy to deploy across Linux, macOS, and Windows.

Typical use cases span several domains:

1. Real‑estate analytics – quickly assess parcel sizes and locations for investment decisions.
2. Urban planning – retrieve cadastral boundaries to evaluate zoning compliance or development potential.
3. Environmental monitoring – identify land parcels that meet specific area thresholds for conservation projects.
4. Legal and tax services – provide clients with authoritative parcel data needed for property disputes or taxation assessments.

Integration into AI workflows is straightforward: once the server is registered, an assistant can invoke or as if they were native tools. The assistant handles the conversational context, while MCPTRINV performs the external lookup and returns structured JSON results that can be parsed or displayed by the client application. This decoupling allows developers to focus on higher‑level logic—such as aggregating results, generating visual maps, or triggering alerts—without managing the complexities of geospatial data retrieval.

What sets MCPTRINV apart is its tight coupling with a trusted public cadastral source (TRINV) and the simplicity of exposing that data through MCP. Developers gain immediate access to reliable, up‑to‑date land information within a familiar AI assistant environment, reducing development time and increasing the robustness of location‑based features.