# Florida GIO Open Data MCP Server (`rl1987/fl-gio-mcp`) Actor

MCP server exposing the Florida GIO (geodata.floridagio.gov) open geospatial data portal to AI agents.

- **URL**: https://apify.com/rl1987/fl-gio-mcp.md
- **Developed by:** [R.L.](https://apify.com/rl1987) (community)
- **Categories:** MCP servers, Real estate
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 price for completing a tool calls

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

### Florida GIO Open Data MCP Server

An [MCP](https://modelcontextprotocol.io) server that lets AI agents search and query the [Florida GIO open data portal](https://geodata.floridagio.gov/) — the Florida Geographic Information Office's public catalog of ~200 state geospatial datasets (boundaries, environment, transportation, imagery, hydrography, and more).

It talks directly to the portal's public DCAT-US catalog feed for dataset discovery and to each dataset's own Esri ArcGIS GeoServices REST API for live feature data, so setup is zero-config: no Florida GIO account, no API key.

#### Coverage

| Tool | What it does |
| --- | --- |
| `search_datasets` | Keyword search across the full catalog (title, description, tags) |
| `get_dataset` | Full metadata for one dataset, incl. every available download format (GeoJSON, Shapefile, CSV, KML, File Geodatabase, GeoPackage, Excel, ...) |
| `get_layer_info` | Field names, types, and geometry type for an ArcGIS FeatureServer/MapServer layer |
| `query_features` | Starts a feature query against a layer (SQL-92 `where` clause and/or spatial filter); returns a `job_id` |
| `get_query_result` | Polls a `query_features` job; returns the result as GeoJSON once done |

Typical flow: `search_datasets("wetlands")` → `get_dataset(id)` to get the `featureServiceUrl` → `get_layer_info(url)` to see field names → `query_features(url, where="county='LEON'")` to start the query → `get_query_result(job_id)` to fetch matching records.

#### Caveats

- The catalog is cached in-memory for 15 minutes per Actor instance to avoid re-fetching the ~200-dataset feed on every `search_datasets`/`get_dataset` call.
- `query_features` runs asynchronously because some ArcGIS layers (especially large statewide ones) can take well over a minute to answer a filtered query — synchronous MCP tool calls would otherwise block or time out. Poll `get_query_result` until `status` is `done` or `error`. Job results are kept for 30 minutes.
- `query_features`/`get_layer_info` proxy straight to the dataset's own ArcGIS server — result caps, field names, and query support (e.g. spatial filters) vary by dataset the same way they would if you queried the ArcGIS REST endpoint directly. Large unindexed text-field filters (e.g. a city-name `where` clause on a statewide parcel layer) can be slow or fail server-side; a spatial (`geometry`) filter combined with an indexed numeric field is usually faster.
- Some catalog entries are external federal layers (e.g. NOAA-hosted) surfaced through the Florida GIO portal rather than Florida-hosted data — `get_dataset` shows the true `featureServiceUrl` host either way.

#### How to connect

Find the Actor's Standby endpoint URL on its **API** tab in Apify Console (shape: `https://rl1987--fl-gio-mcp.apify.actor/mcp`).

Add it with the Claude Code CLI:

```bash
claude mcp add --transport http florida-gio https://rl1987--fl-gio-mcp.apify.actor/mcp \
  --header "Authorization: Bearer $APIFY_TOKEN"
```

`$APIFY_TOKEN` is your own [Apify API token](https://console.apify.com/account/integrations), not the Actor owner's. Verify the connection and tool count with `claude mcp list` or `/mcp` inside Claude Code.

A team can share a `.mcp.json` with just the URL committed to a repo; each teammate runs `claude mcp add --scope local` once with their own token.

#### Output shape

`search_datasets` returns:

```json
{
  "total": 119,
  "results": [
    {
      "id": "https://www.arcgis.com/home/item.html?id=...",
      "title": "Water Level Prediction Stations",
      "landingPage": "https://geodata.floridagio.gov/datasets/fedmaps::water-level-prediction-stations",
      "keyword": ["water level", "tide", "..."],
      "modified": "2026-08-10T05:52:41.962Z",
      "spatial": "-179.81,-29.25,179.97,71.36",
      "featureServiceUrl": "https://services2.arcgis.com/.../FeatureServer/0"
    }
  ]
}
```

`get_dataset` returns the raw DCAT-US record for that item (all `distribution` download links included). `get_layer_info` returns `{name, geometryType, fields}`. `query_features` returns `{job_id, status: "running"}`. `get_query_result` returns `{status: "running"}` while pending, or once done `{status: "done", featureCollection, truncated, feature_count}` where `featureCollection` is a standard GeoJSON `FeatureCollection`.

#### Pricing

Pay-per-event: see [`.actor/pay_per_event.json`](.actor/pay_per_event.json) for the current price per completed tool call (`tool-call` event) — for `query_features`, the charge fires once the job completes successfully, not when it's started. Failed calls are not charged.

#### Data source

All data is sourced live from [Florida GIO](https://geodata.floridagio.gov/): the DCAT-US catalog feed for discovery, and each dataset's own ArcGIS GeoServices REST API for feature queries. Refer to the portal for licensing terms of individual datasets.

#### Resources

- [What is Anthropic's Model Context Protocol?](https://blog.apify.com/what-is-model-context-protocol/)
- [How to use MCP with Apify Actors](https://blog.apify.com/how-to-use-mcp/)
- [FastMCP documentation](https://gofastmcp.com/getting-started/welcome)
- [Apify SDK documentation](https://docs.apify.com/sdk/python/)
- [ArcGIS REST API reference](https://developers.arcgis.com/rest/services-reference/enterprise/query-feature-service-layer/)

#### Did you find this useful?

⭐ Rate this actor on Apify! Your feedback helps other users find it and helps us keep improving it.

# Actor input Schema

## Actor input object example

```json
{}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("rl1987/fl-gio-mcp").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("rl1987/fl-gio-mcp").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call rl1987/fl-gio-mcp --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,rl1987/fl-gio-mcp"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/MtEUftLCHEYeipg48/builds/abkUD5PHyAvKqsVGT/openapi.json