DeepPVMapper

Install

Works with Claude Code, VS Code, Cursor, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install connector/gabrielkasmi-deeppvmapper

About

Use cases: data-analysis

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Permissions

What this server can do and what it asks for, from its tool list, install config and code. Checked Oct 25, 2026.

Tools

17 read · 0 write · 0 deleteRead-only

Secrets

None asked for

Install scripts

Nothing to install (hosted)

Runs as

Hosted (remote endpoint)

Tools (17)

As the server listed them on Oct 25, 2026. Descriptions are the server’s own words; hidden characters are shown as [U+…].

• aggregate_detection_capacity

  Compute the total estimated installed capacity (kWp) and count of detections matching a set of filters — département, commune, capacity range, and cross-validation across sources (cross_validated) or imagery vintages (min_vintages) — plus a quality_summary for the summed sample. Unlike get_department_capacity_stats, which is a fixed pre-computed département-wide aggregate with no other filters, this tool sums a live filtered subset, up to max_rows detections. Example: "installed capacity in Gironde confirmed by at least two sources" -> dpt="33", cross_validated=true. Data quality note: this is…

• count_detections

  Count detections matching a set of filters, exactly, without downloading rows (fast, no row cap). Use this for "how many ..." questions, e.g. "how many installations have an RNB id?" -> has_rnb_id=true; "how many are identified by 2+ sources?" -> quality_filter=true; "how many come from OpenStreetMap?" -> sources_include=[2]. Returns the matching count, the unfiltered registry total and the percentage. Counts are DETECTED systems, not an inventory. Data quality note: this is a detection dataset, not an exhaustive inventory (estimated recall ~0.6). A missing detection does not mean no PV instal…

• get_community_activity

  Get a snapshot of ongoing community contribution activity on the map: how many corrections are currently pending moderation, their breakdown by action type (add / modify / delete), and the most recent submissions (timestamp, action, target). Submitted free-text comments are intentionally excluded from this tool. This reflects unmoderated, unverified user activity, not the registry itself — do not present it as confirmed detection data.

• get_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 the registry yet?" Two independent filters: dpt finds pending edits/deletions (action=modify/delete) targeting existing detections in that département; a full bounding box (min_lon/min_lat/max_lon/max_lat) finds pending new additions (action=add) whose proposed footprint centroid falls inside it. Combine with get_department_capacity_stats / search_detections / get_detections_in_bbox for the confirmed registry picture, and present this separately and clearly …

• get_data_quality_reference

  Return the DeepPVMapper/OpenPVMapper registry's documented data-quality characteristics: estimated detection recall, which fields are model-derived estimates vs. structural/observed fields, the source-encoding table, the recommended confidence threshold, confidence signals, and licensing/liability terms. Call this before advising how much to trust a result for a specific use case (e.g. exploratory research vs. a commercial or regulatory decision) — pair it with the quality_summary attached to search_detections / aggregate_detection_capacity results, which reflects the specific query rather tha…

• get_department_capacity_stats

  Get installed rooftop-PV capacity (total kWp) and system counts for one or all French départements, from the DeepPVMapper/OpenPVMapper registry. This is a fixed, pre-computed department-wide aggregate with no other filters — use aggregate_detection_capacity instead if you need a filtered subset (e.g. only cross-validated detections). Data quality note: this is a detection dataset, not an exhaustive inventory (estimated recall ~0.6). A missing detection does not mean no PV installation exists there. kwp, surface, tilt and azimuth are model estimates, not surveyed values. In this server, quality…

• get_department_profile

  One-call profile of a département: installed capacity and national rank, yearly trend (by first-seen imagery year), source mix, share identified by 2+ sources, and share matched to an RNB building id. Cross-references the pre-computed department statistics with live counts. Data quality note: this is a detection dataset, not an exhaustive inventory (estimated recall ~0.6). A missing detection does not mean no PV installation exists there. kwp, surface, tilt and azimuth are model estimates, not surveyed values. In this server, quality_filter=true keeps only detections identified by 2 or more so…

• get_department_yearly_stats

  Get yearly system counts and capacity by département, based on first-seen imagery year. Useful for tracking apparent PV deployment growth over time. Data quality note: this is a detection dataset, not an exhaustive inventory (estimated recall ~0.6). A missing detection does not mean no PV installation exists there. kwp, surface, tilt and azimuth are model estimates, not surveyed values. In this server, quality_filter=true keeps only detections identified by 2 or more sources (see source_encoding in get_data_quality_reference). Call get_data_quality_reference for the full picture before assessi…

• get_detection_details

  Get the full record of one detection by id: technical characteristics (surface, kwp, tilt, azimuth — model estimates), imagery years, sources decoded into plain labels, frpv_proba, false-positive flag, rnb_id and location codes, plus simple confidence signals. Data quality note: this is a detection dataset, not an exhaustive inventory (estimated recall ~0.6). A missing detection does not mean no PV installation exists there. kwp, surface, tilt and azimuth are model estimates, not surveyed values. In this server, quality_filter=true keeps only detections identified by 2 or more sources (see sou…

• get_detections_in_bbox

  Get rooftop-PV detections within a geographic bounding box (WGS84 lon/lat), including footprint geometry. Intended for map-style spatial queries over a small area. Data quality note: this is a detection dataset, not an exhaustive inventory (estimated recall ~0.6). A missing detection does not mean no PV installation exists there. kwp, surface, tilt and azimuth are model estimates, not surveyed values. In this server, quality_filter=true keeps only detections identified by 2 or more sources (see source_encoding in get_data_quality_reference). Call get_data_quality_reference for the full picture…

• get_field_coverage

  Completeness report: for each optional field of the registry (rnb_id, frpv_proba, false_positive, false_positive_source), how many detections have it filled in and what percentage. Answers "how many installations have an RNB id / an FRPV comparison / a false-positive flag?" in one call, for France or one département. For a single filtered count use count_detections instead. Null means "not available/recorded", never "0" or "confirmed ok". Data quality note: this is a detection dataset, not an exhaustive inventory (estimated recall ~0.6). A missing detection does not mean no PV installation exi…

• get_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 département. Answers "how are installations distributed by size / tilt / orientation / year?". kwp, surface, tilt and azimuth are model estimates. first_seen/last_seen are imagery years, not installation dates. Data quality note: this is a detection dataset, not an exhaustive inventory (estimated recall ~0.6). A missing detection does not mean no PV installation exists there. kwp, surface, tilt and azimuth are model estimates, not surveyed values. In this s…

• get_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, and which tool filters or reports it. Call this when the user asks what a field means or how reliable it is.

• get_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 or all of France, with human-readable labels. A detection can carry several sources, so per-source counts overlap and do not add up to the total. Also returns how many detections are identified by 2+ sources (the meaning of quality_filter). Data quality note: this is a detection dataset, not an exhaustive inventory (estimated recall ~0.6). A missing detection does not mean no PV installation exists there. kwp, surface, tilt and azimuth are model estimates, …

• get_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 data comes from (with references: code, thesis, papers). Use it for questions like "what is FRPV?", "where does the OSM data come from?", "what is a manual correction?". The `sources` field answers "where do we have this installation?": each listed code is a dataset or process that contains it. Example: "0,1" = present in both DeepPVMapper (DPVM) and FRPV; "0,2" = present in DeepPVMapper and OpenStreetMap.

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Stars

37

Forks

4

Open issues

10

Contributors

2

Last commit (this folder)

Oct 18, 2026 (10 days ago)

Last release

Sep 25, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name

io.github.gabrielkasmi/deeppvmapper

Version

0.1.0

Auth

Auth not stated

License

MIT

Repository

github.com/gabrielkasmi/deeppvmapper

Website

deeppvmapper.fr

First seen

Oct 24, 2026

Last checked

Oct 24, 2026

Source

Official MCP Registrygithub-graphql