Geocontext
Provides spatial context to Large Language Models by integrating geographic data services from the Géoplateforme.
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Geocontext is an experimental Model Context Protocol (MCP) server designed to bridge the gap between Large Language Models (LLMs) and rich geographic data. LLMs often struggle with accurate spatial reasoning, leading to plausible but incorrect answers for location-based queries. This tool addresses this by making data and services from the French Géoplateforme (such as geocoding, altitude, administrative, cadastral, and urban planning information) directly accessible to LLMs, delivering precise and context-aware spatial insights without duplicating data or overwhelming models with large, complex responses.
Características Principales
- Geocoding and reverse geocoding capabilities to convert location names to coordinates and vice versa.
- Optimized data responses to minimize token usage for LLMs and reduce the likelihood of hallucinations.
- Altitude retrieval for any given geographic coordinates from specialized services.
- Ability to query and explore Géoplateforme Web Feature Service (WFS) tables, including searching types, describing schemas, and retrieving feature data.
- Comprehensive access to administrative (commune, département, région), cadastral, and urban planning (PLU, POS) information for locations.
- 4 GitHub stars
Casos de Uso
- Augment LLM conversations with precise geographic context, such as determining the exact coordinates or altitude of a place.
- Allow LLMs to explore and retrieve specific feature data, for example, identifying buildings within a certain radius or listing bridges of a particular type from national geographic databases.
- Enable LLMs to obtain detailed spatial information like administrative boundaries, land parcel details, or urban regulations for any queried point.
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