data.gouv.fr's Albert-Powered AI Metadata Enrichment and Natural-Language Catalogue Access

Etalab, the French digital administration agency inside DINUM (Direction interministérielle du numérique), has added generative-AI features to data.gouv.fr, the national open-data portal, as part of the platform's 2025 evolution roadmap.
The features rely on Albert, a French state-hosted open large language model: it auto-generates short descriptions for datasets whose producers haven't written one, and suggests keywords and tags drawn from existing metadata to improve catalogue completeness. The portal was also connected to an MCP (Model Context Protocol) server, letting external AI assistants such as Claude, ChatGPT or Mistral query the dataset catalogue directly in natural language.
Etalab has not published adoption or accuracy statistics for these features, and describes the work as experimental and iterative rather than a finished, measured product — its own documentation states plainly that 'suggestions from LLMs may be incomplete, approximate, or wrong' and that human validation is required before publishing.
Independent French tech-and-data coverage (samsa.fr) has flagged a related security caveat: fake MCP servers impersonating data.gouv.fr have already appeared online, underlining that opening a government data catalogue to LLM querying carries new risks that the practice's evaluation should weigh alongside its convenience gains.

Read the full analysis: https://www.data.gouv.fr/posts/quelles-evolutions-de-la-plateforme-en-2025