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Open registry of 1.14M+ rooftop-solar detections across France, queryable by natural language.
Remote server: your requests and data go to zelhliylrlktnasircwp.supabase.co. Claude Code: claude mcp add --transport http deeppvmapper https://zelhliylrlktnasircwp.supabase.co/functions/v1/mcp/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
get_data_quality_reference — Return the DeepPVMapper/OpenPVMapper registry's documented data-quality characteristics: estimated detection recall, which fields are model-get_department_capacity_stats — Get installed rooftop-PV capacity (total kWp) and system counts for one or all French départements, from the DeepPVMapper/OpenPVMapper regisget_department_yearly_stats — Get yearly system counts and capacity by département, based on first-seen imagery year. Useful for tracking apparent PV deployment growth ovsearch_detections — Search individual rooftop-PV detections by département, commune (INSEE code), estimated capacity range, and/or cross-validation confidence (aggregate_detection_capacity — Compute the total estimated installed capacity (kWp) and count of detections matching a set of filters — département, commune, capacity rangget_detections_in_bbox — Get rooftop-PV detections within a geographic bounding box (WGS84 lon/lat), including footprint geometry. Intended for map-style spatial queget_community_activity — Get a snapshot of ongoing community contribution activity on the map: how many corrections are currently pending moderation, their breakdownget_community_activity_in_area — Find pending, unmoderated community contributions relevant to a specific area, to answer "has anyone flagged anything here that is not in thcount_detections — Count detections matching a set of filters, exactly, without downloading rows (fast, no row cap). Use this for "how many ..." questions, e.gget_source_breakdown — Break down detections by source code (0=DPVM pipeline, 1=FRPV reference, 2=OSM, 3=manual correction, 4=recall sample), for one département oget_detection_details — Get the full record of one detection by id: technical characteristics (surface, kwp, tilt, azimuth — model estimates), imagery years, sourceget_department_profile — One-call profile of a département: installed capacity and national rank, yearly trend (by first-seen imagery year), source mix, share identiget_field_coverage — Completeness report: for each optional field of the registry (rnb_id, frpv_proba, false_positive, false_positive_source), how many detectionget_field_distribution — Histogram of a numeric field (kwp, surface, tilt, azimuth, n_vintages, first_seen, last_seen) with exact counts per bin, for France or one dget_field_reference — Field-by-field documentation of a detection record: type, unit, nullability, whether it is observed or a model estimate, how to read it, andget_source_reference — Explain the data sources behind the registry's `sources` field: for each source, its code, short key, name, accepted aliases, and where the get_started — START HERE. Call this first when the user is new, asks what this server can do, or asks a vague question about DeepPVMapper. Returns a plainNot tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.