arcgis-mcp
Enables querying and metadata retrieval from ArcGIS REST services, allowing users to interact with geospatial data layers through natural language.
README
arcgis-mcp
Generic MCP connector for querying ArcGIS REST services - built so it works against RRC's well/pipeline data today, and your own ArcGIS Online account later (once you have a login), without any code changes.
Why generic, not hardcoded to one URL
RRC's own statewide GIS service (gis.rrc.texas.gov) exists but its exact
service path wasn't confirmed directly (an automated-access block on that
one page stopped me checking it myself). What is confirmed and verified
live is a regional mirror of the same TXRRC well/pipeline data, hosted by
Houston-Galveston Area Council - see KNOWN_SERVICES in
src/arcgis_client.py. That mirror's extent suggests Houston-area coverage
rather than confirmed statewide, so treat it as a starting point, and swap
in RRC's real statewide URL the moment you confirm it (same tool works
against any ArcGIS REST MapServer/FeatureServer URL).
Tools exposed
list_known_services()- pre-verified service URLs and layer notes.get_layer_metadata(service_url, layer_id?, token?)- field names, geometry type, extent for a service or one layer in it. Call this first against any new/unknown service so you know what to filter on.query_arcgis_layer(service_url, layer_id, where, out_fields, bbox?, token?)- runs a standard Esri REST query, returns GeoJSON.
tokenis optional and only needed for private/ArcGIS Online services later.
- runs a standard Esri REST query, returns GeoJSON.
Verified so far
get_layer_metadata was checked directly against the live HGAC TXRRC/Wells
service and returned real field names (API, WELLID, LONG83, LAT83,
etc. on the Surface Wells layer). The actual query_arcgis_layer data call
follows the standard, widely-documented Esri REST query spec, but wasn't
hit live before handoff - it should work as-is; if a response looks off,
send me the error/output and I'll adjust.
Run locally
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python main.py
Test:
curl -X POST http://localhost:3000/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"query_arcgis_layer","arguments":{"service_url":"https://www.gis.hctx.net/arcgishcpid/rest/services/TXRRC/Wells/MapServer","layer_id":0,"where":"1=1","out_fields":"API,WELLID","bbox":"-96.9,29.0,-96.5,29.4"}}}'
Deploy
Same pattern as before:
git init && git add . && git commit -m "Initial ArcGIS MCP connector"
git remote add origin https://github.com/<you>/arcgis-mcp.git
git push -u origin main
Render dashboard -> New -> Blueprint -> point at the repo (picks up
render.yaml) -> deploy. Endpoint will be
https://arcgis-mcp.onrender.com/mcp.
Adding your own ArcGIS Online account later
Once you have a login: generate a token (ArcGIS Online -> your account ->
generate API key/token, or OAuth if you want it to expire/refresh), then
pass it as the token argument on query_arcgis_layer /
get_layer_metadata calls against your own hosted feature layers - no
redeploy needed, it's just a per-call argument.
Combining with Enverus isopach data
This connector only fetches ArcGIS layers (wells, pipelines, or whatever else you point it at). Combining that with Enverus's isopach output into one map happens at the chat level - ask Claude to pull both and render them together once you're connected to this and have wells/pipelines to overlay.
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