Connect Gisgp and your agent gets 104 tools, among them analyze_location, assess_airspace_obstruction_proximity, assess_datacenter_site. It answers at https://gisgp.com/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 6 of 6 times since 11 September 2026; the last check, on 24 October 2026, succeeded.
GIS tools for AI agents: 65 free tools + 8 paid (hazard/site-scouting/GeoJSON export)
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
analyze_location | Reverse-geocode a WGS84 point to country/region/locality via OSM Nominatim (no key, free — fair-use rate limited, best-effort). Returns JSON: {ok, display_name, country, country_code, region, locality, source}. Inputs: lon, lat |
assess_airspace_obstruction_proximity | PAID (100 credits) — nearby FAA-registered vertical obstructions (towers, stacks, wind turbines) at a US point, for telecom/tower-siting due diligence (e.g. "is there anything tall already near this proposed tower site", "does a 250ft tower Inputs: lon, lat, proposed_height_agl_ft |
assess_datacenter_site | PAID (300 credits) — data center site-scouting composite: grid proximity (power availability), multi-source hazard (seismic + FEMA + NOAA, required — same contract as assess_property_hazard), land cover, and a year of temperature history (c Inputs: lon, lat |
assess_energy_community_credit | PAID (100 credits) — US Inflation Reduction Act "energy community" bonus tax credit qualification lookup for a renewable energy project site. Checks both DOE/NETL-published qualifying pathways (coal-mine- closure/coal-plant-retirement adjoi Inputs: lon, lat |
assess_ev_charging_site | One-call EV charging site-scouting indicator: grid proximity (power for fast-charging) + land cover + locality context, combined from GISGP's existing free primitives. No key needed. Returns JSON: {ok, grid_proximity, land_cover, location, Inputs: lon, lat |
assess_grid_exposure | Electric grid infrastructure proximity at a US point: nearby substations + transmission lines within 10 miles (community ArcGIS mirror of HIFLD data — proximity indicator, not a certified survey). No key needed. Returns JSON: {ok, substatio Inputs: lon, lat |
assess_pipeline_proximity | Natural gas interstate/intrastate transmission pipeline proximity at a US point (EIA/HIFLD, 32,892 segments). Substitute for proprietary local-utility "call before you dig" data — covers major transmission pipelines only, NOT local distribu Inputs: lon, lat |
assess_portfolio_climate_disclosure | PAID (200 credits PER PROPERTY, max 25 properties/call) — bulk physical climate-risk disclosure input for a real-estate/asset portfolio (SEC climate disclosure rule / EU CSRD physical-risk reporting). Runs assess_property_hazard for each [l Inputs: properties |
assess_property_hazard | PAID (200 credits) — multi-source US property hazard indicator: USGS seismic risk (required), plus best-effort FEMA disaster declaration history (state, last 10 years) and NOAA real-time active severe weather alerts at the point. Requires A Inputs: lon, lat |
assess_property_hazard_x402 | PAID via x402 (USDC on Base Sepolia testnet, ~$0.20/call) — no GISGP account or API key needed, the agent pays directly on-chain. Multi-source US property hazard indicator (USGS seismic + FEMA disaster history + NOAA active alerts), same un Inputs: lon, lat |
assess_protected_area_proximity | US protected/conservation area proximity via USGS PAD-US (public domain, commercial-use OK — unlike Protected Planet/WDPA, whose API explicitly forbids commercial-entity use). Reports whether the point falls inside/near (2 mile radius) a fe Inputs: lon, lat |
assess_reforestation_site | PAID (100 credits) — reforestation/afforestation site-scouting composite: terrain, land cover (flags already-forested/urban/water/snow as unsuitable), and a year of precipitation history (tree-viability proxy). All-free-primitive composite, Inputs: lon, lat |
assess_renewable_site | One-call solar/wind site-scouting indicator: terrain + land cover + 1-year solar/wind climate averages + grid proximity, combined from GISGP's existing free primitives (no new external source). No key needed. Returns JSON: {ok, terrain, lan Inputs: lon, lat |
assess_site_due_diligence | PAID (300 credits) — master due-diligence report for a point: wraps assess_property_hazard (seismic + FEMA + NOAA, required) plus grid proximity, land cover, and reverse-geocoded locality — all in one call. No invented overall "site score" Inputs: lon, lat |
assess_supply_chain_redundancy | PAID (400 credits) — checks whether two supposedly-redundant sites (e.g. two "backup" suppliers/warehouses/data centers) are actually independent: real geodesic distance between them + each site's own multi-source hazard profile (seismic + Inputs: site_a, site_b |
assess_telecom_site | One-call cell tower site-scouting indicator: grid proximity + terrain elevation (line-of-sight proxy) + land cover, combined from GISGP's existing free primitives. No key needed. Returns JSON: {ok, grid_proximity, terrain, land_cover, physi Inputs: lon, lat |
assess_wildfire_risk | Real-time active wildfire proximity at a point via NASA FIRMS (VIIRS satellite hotspot detections, last 2 days) + electric grid exposure (transmission lines are a documented wildfire-ignition- liability factor). No key needed — GISGP holds Inputs: lon, lat |
audit_service | Full one-call QA report of an ArcGIS FeatureServer layer: health (latency, record count, capabilities) + field schema + coded domains + summary counts. One call replaces separate health/fields/domains lookups. Returns JSON: {name, geometry_ Inputs: service_url, token |
buffer_geojson | Buffer every feature by a distance in METRES (negative shrinks). Geodesically accurate at any latitude (each feature is buffered in a local equidistant projection). Returns JSON {ok, distance_m, geojson} where geojson is a FeatureCollection Inputs: geojson, distance_m |
bundle_create_export_schedule | PAID PER DELIVERY (30 credits each time it fires, NOT at creation — free to create/cancel) — the only MCP tool that exposes GISGP's core recurring-export product to agents: creates a schedule that re-exports a FeatureServer layer on its own Inputs: service_url, format, webhook_url, frequency, where, run_hour |
bundle_export_fixed | PAID (150 credits) — fetch ALL records from a live FeatureServer layer (no 50-record preview cap), auto-repair invalid geometries (GEOS make_valid), and scan for common problems, in one call. Replaces an uncapped query_features call (itself Inputs: service_url, where, token |
bundle_export_multi_format | PAID (120 credits) — fetch ALL records from a live FeatureServer layer once, then export the same data as Shapefile + CSV + GeoJSON + KML + Excel in a single ZIP (base64-encoded). Replaces an uncapped fetch plus 4 separate format-conversion Inputs: service_url, where, token |
bundle_geocode_enrich | PAID (30 credits PER ADDRESS, max 10 addresses/call) — batch geocode + enrich. For each address: forward-geocodes to lon/lat (free fallback chain: OSM Nominatim -> Photon -> US Census), then reverse-geocodes for country/region/locality cont Inputs: addresses |
bundle_migrate_convert | PAID (40 credits) — one-call file migration: convert a raw file to GeoJSON, then optionally reproject and simplify, then round coordinates. Replaces 2-4 separate free tool calls (convert + reproject + simplify + round) an agent would otherw Inputs: input_format, data, to_epsg, simplify_tolerance, round_decimals |
bundle_migration_readiness | PAID (100 credits) — migration-readiness report comparing two FeatureServer layers: schema diff, coded-value domains, and field types for both. Replaces compare_schemas + extract_domains×2 + check_field_types×2. Requires Authorization: Bear Inputs: service_url_a, service_url_b, token_a, token_b |
calculate_route | Real driving distance + duration between two points. Default: OSRM (public demo instance, no key — fair-use limited, not a production SLA). Optional agol_token: route through Esri's own World Route Service instead — uses YOUR OWN AGOL crede Inputs: origin_lon, origin_lat, dest_lon, dest_lat, agol_token |
cancel_export_schedule | FREE — cancel a schedule created by bundle_create_export_schedule. Only the API key that created it can cancel it. Returns JSON: {ok} or {ok: false, error}. Inputs: schedule_id, token |
centroids_geojson | Get the center point of each polygon/line feature — e.g. "find the center of each parcel", "convert polygons to points for labeling", "centroid of each feature". Properties are kept. Returns JSON {ok, geojson} — a FeatureCollection of point Inputs: geojson |
check_field_types | Inspect the field schema of an ArcGIS FeatureServer layer. Returns JSON: {layer_name, geometry_type, fields:[{name, alias, type, length, nullable, has_domain}]} — useful before importing/mapping data. Inputs: service_url, token |
check_service_health | Check whether an ArcGIS FeatureServer layer is reachable and responsive. Returns JSON: {ok, ms (latency), name, geometry_type, field_count, record_count, capabilities, max_record_count}. Inputs: service_url, token |
check_wallet_balance | FREE — check your own MCP credits wallet balance (the same account paid tools like assess_property_hazard charge against). Requires Authorization: Bearer <api_key> — an agent can call this on its own, no browser/dashboard needed. Returns JS |
classify_land_cover | Land cover class at a WGS84 point via ESA CCI Land Cover 2018 (ArcGIS Living Atlas ImageServer, no key, 300m resolution). Returns JSON: {ok, class_code, class_label, source}. NOTE 2026-07-26: gated separately (mcp_layer1_landcover, Off pend Inputs: lon, lat |
compare_schemas | Compare the field schemas of two ArcGIS FeatureServer layers. Returns JSON diff: {added, removed, changed:[{field, diffs}], same, geometry_match, identical} — useful for QA before an import or migration. Inputs: service_url_a, service_url_b, token_a, token_b |
convert_coordinates | Convert coordinate pairs between EPSG coordinate systems (max 1000 points). points: [[x, y], ...] in from_epsg axis order (lon/lat for EPSG:4326). Returns JSON: {"points": [[x, y], ...], "from_epsg": ..., "to_epsg": ...}. Inputs: points, from_epsg, to_epsg |
convex_hull_geojson | Draw the smallest polygon that wraps around all input features (a convex hull) — e.g. "draw a boundary around these points", "find the outer perimeter of my data", "convex hull of these locations". Returns JSON {ok, geojson} — a single poly Inputs: geojson |
count_features | Count features in an ArcGIS FeatureServer layer, optionally filtered by a WHERE clause. service_url: full layer URL ending in /FeatureServer/<n>. token: only for private layers. Returns JSON: {"ok": true, "count": ..., "name": ..., "geometr Inputs: service_url, where, token |
csv_to_geojson | Convert a CSV/spreadsheet with lat/lon (or X/Y) columns to GeoJSON — auto-detects the coordinate columns (e.g. "map this spreadsheet", "CSV with lat/lon to GeoJSON", "turn my Excel export into map points"). Returns a GeoJSON FeatureCollecti Inputs: csv |
csv_to_gpx | Convert a CSV with latitude/longitude columns directly to GPX waypoints (2026-09-03) — e.g. "these coordinates to a GPX for my GPS". Column names are auto-detected (lat/latitude/y, lon/lng/longitude/x). Inputs: csv |
detect_coordinate_order | Detect whether [x, y] pairs are [lon, lat] or [lat, lon] — resolves a genuinely common real-world confusion (one of the most-viewed GIS StackExchange questions ever, 550k+ views). Certain when any value exceeds ±90 (only longitude can); hon Inputs: points |
discover_open_geodata | Keyword search across ArcGIS Hub Open Data — real public FeatureServer/MapServer datasets from government/organization ArcGIS Online portals worldwide. Returns real service_url values usable directly with query_features/count_features/rest_ Inputs: query, limit |
discover_open_geodata_pro, dissolve_geojson, dxf_to_geojson, dxf_to_pdf_report, embed_map_snippet, envelope_geojson, epsg_suggest, estimate_cost, export_geojson_to_excel, export_geojson_to_pdf, extract_domains, find_layer_issues, fix_geometry, flatgeobuf_to_geojson, full_service_audit, generate_static_map_image, geocode_address, geojson_diff, geojson_to_csv, geojson_to_dxf, geojson_to_flatgeobuf, geojson_to_gpx, geojson_to_kml, geojson_to_mapinfo_tab, geojson_to_shapefile, geojson_to_wkt, geometry_health_report, geometry_stats, georeference_dxf, get_climate_history, get_elevation_profile, get_river_flow_status, get_terrain_profile, gpx_to_csv, gpx_to_geojson, gpx_to_kml, gpx_to_shapefile, grade_service, guess_crs_from_coordinates, kml_to_geojson, kml_to_gpx, kml_to_shapefile, list_dxf_layers, mapinfo_tab_to_geojson, minimum_rotated_rectangle, nearest_features_geojson, offset_coordinates, overlay_geojson, query_features, query_statistics, rank_hazard_safe_sites, rank_renewable_sites, reduce_precision, reproject_geojson, rest_explore, shapefile_to_geojson, shapefile_to_gpx, share_map, simplify_geometry, spatial_join_geojson, tile_math, validate_geojson, voronoi_geojson, wkt_to_geojson
Every block below points at https://gisgp.com/mcp. Pick your client and copy.
claude mcp add --transport http gisgp https://gisgp.com/mcp
{
"mcpServers": {
"gisgp": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://gisgp.com/mcp"]
}
}
}{
"mcpServers": {
"gisgp": {
"url": "https://gisgp.com/mcp"
}
}
}{
"servers": {
"gisgp": {
"type": "http",
"url": "https://gisgp.com/mcp"
}
}
}{
"context_servers": {
"gisgp": {
"url": "https://gisgp.com/mcp"
}
}
}{
"mcpServers": {
"gisgp": {
"serverUrl": "https://gisgp.com/mcp"
}
}
}{
"mcpServers": {
"gisgp": {
"url": "https://gisgp.com/mcp"
}
}
}name: Gisgp
version: 0.0.1
schema: v1
mcpServers:
- name: Gisgp
type: streamable-http
url: https://gisgp.com/mcp{
"mcpServers": {
"gisgp": {
"httpUrl": "https://gisgp.com/mcp"
}
}
}{
"mcpServers": {
"gisgp": {
"type": "http",
"url": "https://gisgp.com/mcp"
}
}
}{
"mcpServers": {
"gisgp": {
"url": "https://gisgp.com/mcp"
}
}
}goose://extension?url=https%3A%2F%2Fgisgp.com%2Fmcp&type=streamable_http&id=gisgp&name=Gisgp
It answered our last check on 24 October 2026 in 372 ms. Over 6 checks since 11 September 2026 it answered 6. Status here comes from Neuronto's own probes, not from the publisher.
104, as returned by the server's own tools/list on 22 September 2026: analyze_location, assess_airspace_obstruction_proximity, assess_datacenter_site, assess_energy_community_credit, assess_ev_charging_site, assess_grid_exposure, assess_pipeline_proximity, assess_portfolio_climate_disclosure, and 96 more.
It answered our last check on 24 October 2026 in 372 ms. Over 6 checks since 11 September 2026 it answered 6.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://gisgp.com/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: io.github.uponex. Endpoint host: gisgp.com. ARD identifier: urn:air:io.github.uponex:mcp:gisgp.
First indexed 10 September 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.