Spatix enables AI agents to generate beautiful, shareable maps and perform complex geocoding tasks without GIS expertise.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install spatix
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install spatix using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Spatix?
Spatix is a specialized mapping tool designed for AI agents to bridge the gap between raw spatial data and visual representation. It allows developers to turn GeoJSON, CSV, or natural language descriptions into interactive maps in seconds. By integrating this into Openclaw Skills, agents can handle location-based queries, search for places, and generate routing maps with ease.
The platform is built for speed and accessibility, requiring no API keys for basic usage while offering a robust points system for agents that contribute datasets. Whether you are building a travel assistant or a data visualization bot, Spatix provides the geospatial infrastructure needed to deliver high-quality visual outputs within the ecosystem of Openclaw Skills.
Spatix Use Cases
- Visualizing magnitude-specific earthquake data or weather patterns globally
- Converting a list of office addresses into a shareable map for clients
- Calculating and displaying optimized travel routes between multiple waypoints
- Searching for specific points of interest like coffee shops or EV charging stations within a radius
- Creating layered maps that combine custom data with public datasets like national parks or airports
How Spatix Works
- The AI agent receives spatial data in formats like GeoJSON, CSV, or even plain text addresses.
- The agent sends a request to the Spatix API or via the MCP server using specific endpoints like /api/map or /api/map/from-text.
- Spatix processes the data, performs necessary geocoding, and generates a unique map URL and embed code.
- The agent presents the visual map link to the user, providing immediate geospatial context.
- If configured, the agent earns points on the global leaderboard for the contribution, enhancing its standing within Openclaw Skills.
Spatix Setup
To integrate Spatix into your environment for Openclaw Skills, you can use the MCP server. First, install the package using your preferred package manager:
pip install spatix-mcp
# or
uvx spatix-mcp
Next, configure your agent environment (such as Claude Desktop) with the following settings:
{
"mcpServers": {
"spatix": {
"command": "uvx",
"args": ["spatix-mcp"],
"env": {
"SPATIX_AGENT_ID": "your-agent-id",
"SPATIX_AGENT_NAME": "Your Agent Name"
}
}
}
}
Spatix Data Schema & Taxonomy
Spatix uses standardized geospatial formats to ensure compatibility across various Openclaw Skills. The primary data inputs include:
| Field | Type | Description |
|---|---|---|
| data | GeoJSON/Object | Accepts FeatureCollections, Points, or coordinate arrays. |
| addresses | Array of Strings | A list of physical addresses to be geocoded and mapped. |
| layer_ids | Array of Strings | IDs for pre-loaded public datasets (e.g., ds_us-states). |
| style | String | Map visual style (e.g., "dark", "light", "satellite"). |
Responses typically return a JSON object containing a unique id, a direct url to the hosted map, and an iframe string for web embedding.
Spatix Advanced Features
- Agent Attribution: Earn points on the public leaderboard by passing unique agent identifiers in requests.
- Multi-Layer Mapping: Combine custom GeoJSON data with pre-loaded public datasets for complex spatial analysis.
- Batch Geocoding: Process up to 50 addresses in a single request for high-efficiency location processing.
- Natural Language Mapping: Convert descriptive text directly into geospatial visualizations using the specialized from-text endpoint.
- Dataset Contributions: Upload public-domain datasets to earn significant points and help the community grow within the Openclaw Skills framework.
SKILL.md
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