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occ-gis-mcp

An MCP (Model Context Protocol) server that gives AI assistants (like Claude, GitHub Copilot, or any MCP-compatible client) access to public GIS datasets from the Oklahoma Corporation Commission's open data hub: https://gisdata-occokc.opendata.arcgis.com/

No coding experience required to set this up. Follow the steps below in order.

What is this, in plain terms?

MCP ("Model Context Protocol") is a standard way for AI chat tools to call small programs ("servers") that fetch live data. This repo is one of those servers. Once it's set up, you can ask your AI assistant things like:

  • "List the datasets available from the OCC GIS hub"

  • "Find all active oil wells in Oklahoma County"

  • "Show me the fields available on the PST Tanks layer"

and the assistant will use this server to fetch real, live answers instead of guessing.

Related MCP server: mcp-arcgis-houston

Step 1 — Install Node.js

This server runs on Node.js. If you don't already have it:

  1. Go to https://nodejs.org

  2. Download the LTS (Long Term Support) version for your operating system.

  3. Run the installer, accepting the defaults.

  4. Confirm it worked by opening a terminal (PowerShell on Windows, Terminal on Mac/Linux) and running:

    node -v
    npm -v

    Both should print a version number (e.g. v20.11.0). If you see an error, restart your terminal/computer and try again.

Step 2 — Download this project

Option A: Using Git (recommended if you have it)

git clone https://github.com/MSPFE2019/occ-gis-mcp.git
cd occ-gis-mcp

Option B: Without Git

  1. Go to https://github.com/MSPFE2019/occ-gis-mcp

  2. Click the green Code button → Download ZIP

  3. Unzip it somewhere you'll remember (e.g. your Documents folder)

  4. Open a terminal and cd into that unzipped folder, for example:

    cd "C:\Users\YourName\Documents\occ-gis-mcp"

Step 3 — Install dependencies

From inside the project folder, run:

npm install

This downloads the small libraries the server needs. You only need to do this once (and again any time the code changes).

Step 4 — Test that it runs

There are two ways to run this server — pick based on where you'll use it:

  • index.js — for local desktop tools (Claude Desktop, VS Code/Copilot Chat).

  • http.js — for remote/cloud tools like Copilot Studio (see the dedicated section below).

Try the local one first:

node index.js

Nothing will print — that's expected! MCP servers talk over a silent input/output channel and just wait for a client to connect. Press Ctrl+C to stop it.

For a more visual test, use the official MCP Inspector, which opens a browser page where you can click buttons and see live results:

npx @modelcontextprotocol/inspector node index.js

This opens a local webpage. Click Connect, then List Tools, then try running list_datasets with no arguments — you should see a list of real datasets come back as JSON. If that works, the server is working correctly.

Step 5 — Connect it to your AI assistant

MCP servers are configured once inside your AI client's settings. Pick the guide that matches your tool:

Claude Desktop

  1. Open Claude Desktop → Settings → Developer → Edit Config (this opens claude_desktop_config.json in a text editor).

  2. Add an entry like this (replace the path with your actual project folder, using double backslashes \\ on Windows):

    {
      "mcpServers": {
        "occ-gis": {
          "command": "node",
          "args": ["C:\\Users\\YourName\\Documents\\occ-gis-mcp\\index.js"]
        }
      }
    }
  3. Save the file and fully restart Claude Desktop.

  4. Ask it: "What OCC GIS datasets are available?"

VS Code (GitHub Copilot Chat) or other MCP-aware editors

  1. Open (or create) an mcp.json file in your MCP settings (in VS Code: Command Palette → "MCP: Open User Configuration", or add it to your workspace's .vscode/mcp.json).

  2. Add the same mcpServers block shown above.

  3. Reload the window and the new tools will appear when you chat with Copilot.

Any other MCP client

Any client that supports the MCP standard accepts the same shape of config: a command (node) and args (the full path to index.js). Consult your client's documentation for where that config file lives.

Available tools

Once connected, your assistant can call these:

Tool

What it does

list_datasets

Search/list the datasets on the hub (wells, tanks, etc.). Optional free-text query.

get_dataset

Full details for one dataset by title, including download links (CSV, GeoJSON, Shapefile, KML, File Geodatabase) and its live ArcGIS service URL.

get_layer_metadata

Field names, geometry type, and extent for a given ArcGIS layer URL.

query_layer

Run attribute (where) and/or spatial queries against a layer and get back matching records.

Customizing for a different ArcGIS Hub site

This server isn't limited to the OCC's data — it works with any ArcGIS Hub site that exposes a DCAT-US catalog feed (most public ArcGIS Hub sites do). To point it at a different site, open server.js and change this line near the top:

const HUB_BASE = "https://gisdata-occokc.opendata.arcgis.com";

to your target site's base URL, then re-run the server. Everything else (tool names, query logic) works the same way.

Connecting to Microsoft Copilot Studio

Copilot Studio doesn't run this server for you — it needs to reach it over the internet as an HTTPS URL. That's what http.js is for (as opposed to index.js, which is only for local tools like Claude Desktop). There are two parts: (A) put the server somewhere reachable on the internet, then (B) register it in Copilot Studio.

A. Deploy the HTTP server somewhere public

Pick whichever is easiest for you — all of them run the same command: npm install then npm run start:http.

Easiest for beginners — Azure App Service (or Azure Container Apps)

  1. Push this repo to your own GitHub account (already done if you're reading this from your fork/copy).

  2. In the Azure Portal, create a Web App → Runtime stack: Node 20 LTS → deploy from your GitHub repo (Azure sets up CI/CD for you).

  3. Under Configuration → Startup Command, set:

    node http.js
  4. Once deployed, Azure gives you a URL like https://occ-gis-mcp.azurewebsites.net. Your MCP endpoint is that URL plus /mcp, e.g. https://occ-gis-mcp.azurewebsites.net/mcp.

Also simple — Render, Railway, or Fly.io Any of these can deploy a Node.js repo from GitHub in a few clicks:

  • Build command: npm install

  • Start command: npm run start:http

  • They'll give you a public https://... URL — again, append /mcp.

Local testing only (not for production)

npm install
npm run start:http

This starts the server at http://localhost:3000/mcp. To test whether Copilot Studio (a cloud service) can reach a server on your own machine, you'd need a tunnel tool like ngrok (ngrok http 3000), which gives you a temporary public HTTPS URL. This is fine for a quick demo, not for real/ongoing use.

B. Register it in Copilot Studio

  1. Open your agent in Copilot Studio → go to Tools (or Actions) → Add a tool → New tool → Model Context Protocol.

  2. Give it a name (e.g. "OCC GIS Data") and paste your server's HTTPS URL including /mcp, e.g. https://occ-gis-mcp.azurewebsites.net/mcp.

  3. Choose No authentication (this server is read-only and doesn't require credentials) unless you've added your own auth layer in front of it.

  4. Save. Copilot Studio will call the server and automatically discover the four tools (list_datasets, get_dataset, get_layer_metadata, query_layer) along with their descriptions — no manual schema entry needed.

  5. Test it in the Copilot Studio test chat pane: ask "What OCC GIS datasets are available?" or "Find active wells in Oklahoma County."

Available tools

Once connected, your assistant can call these:

Tool

What it does

list_datasets

Search/list the datasets on the hub (wells, tanks, etc.). Optional free-text query.

get_dataset

Full details for one dataset by title, including download links (CSV, GeoJSON, Shapefile, KML, File Geodatabase) and its live ArcGIS service URL.

get_layer_metadata

Field names, geometry type, and extent for a given ArcGIS layer URL.

query_layer

Run attribute (where) and/or spatial queries against a layer and get back matching records.

Troubleshooting

  • node: command not found — Node.js isn't installed or your terminal needs restarting after installation. Redo Step 1.

  • Inspector/tool call errors mentioning network/fetch — check your internet connection; the server calls the live ArcGIS Hub API on every request.

  • Assistant doesn't see the new tools — double check the file path (local) or URL (Copilot Studio) is correct, and that you fully restarted/reconnected the client.

  • Copilot Studio says it can't connect — make sure you registered the URL ending in /mcp (not just the bare domain), that the deployment is actually running, and that it's reachable over plain HTTPS (no VPN/firewall blocking it).

Notes

  • The dataset list is pulled live from the hub's DCAT-US catalog feed and cached for 15 minutes to keep things fast.

  • Data is public but subject to the source agency's terms of use (shown in the get_dataset output's license field).

  • http.js runs in stateless mode (a fresh server per request), which keeps hosting simple and is fully compatible with how Copilot Studio calls MCP tools.

Available Tools

4 tools
get_datasetGet OCC GIS dataset detailsA

Get full details for one dataset on the OCC GIS hub by exact or partial title match, including every distribution (ArcGIS REST service URL, CSV/GeoJSON/Shapefile/KML/FileGDB download links), spatial extent, and license text.

Inputs: title (required).

get_layer_metadataGet ArcGIS layer metadataA

Fetch metadata (fields, geometry type, extent, name, description) for an ArcGIS FeatureServer/MapServer layer URL, such as one returned by list_datasets or get_dataset as 'featureServiceUrl'.

Inputs: layerUrl (required).

list_datasetsList OCC GIS datasetsA

List/search datasets published on the OCC GIS open data hub (gisdata-occokc.opendata.arcgis.com). Optionally filter with a free-text query matched against title, description, and keywords. Returns each dataset's title, description, landing page, keywords, and (when available) its ArcGIS FeatureServer/MapServer REST URL plus downloadable formats (CSV, GeoJSON, Shapefile, KML, File Geodatabase).

Inputs: limit, query.

query_layerQuery an ArcGIS layer's featuresA

Run an attribute and/or spatial query against an ArcGIS FeatureServer/MapServer layer (e.g. OCC well points, tank sites) and return matching feature attributes (and optionally geometry) as JSON. Use get_layer_metadata first to see available fields.

Inputs: layerUrl (required), where, geometry, outFields, +5 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4.4/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct role: listing/searching datasets, fetching full dataset details, inspecting layer metadata, and querying layer features. There is no overlap that would confuse an agent selecting among them.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (list_datasets, get_dataset, get_layer_metadata, query_layer), using snake_case throughout and verbs that clearly indicate the action.

    Tool Count5/5

    Four tools is an appropriate scope for a read-only GIS data discovery and query server. Each tool fills a necessary step in the workflow without redundancy or bloat.

    Completeness5/5

    The tool surface fully covers the core workflow: discovering datasets, retrieving full metadata, inspecting layer schemas, and querying features. No obvious dead ends exist; even direct data downloads are covered via distribution URLs returned by the get_dataset tool.

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