How to Use the Nearmap (High-Res Aerial Imagery & AI) MCP in Cline

Q: Can Nearmap (High-Res Aerial Imagery & AI) identify specific roof types in Cline?

Yes. Your agent can call listaifeatureclasses to see the available computer vision categories. It then uses that taxonomy to extract specific roof arrays and solar panels.

Q: How does the agent handle missing survey data?

Cline is smart enough to check first. It runs checkcoveragepolygon to verify aerial survey boundaries. If a region is missing, it will tell you before attempting to write the integration code.

Build geospatial apps faster. Let Cline pull Nearmap aerial data and write the exact code to render it in VS Code.

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Connect Nearmap (High-Res Aerial Imagery & AI) MCP to Cline

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Setup Nearmap (High-Res Aerial Imagery & AI) with Cline

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End-to-End Mapping Components

You tell Cline to build a property viewer dashboard, and it handles the entire stack. It fetches the live data using the `get_vertical_tile` tool, writes the React component, and imports the imagery payload. It then layers on the data. Cline calls `get_ai_detected_features` to grab the vector boundaries for roofs and vegetation, writes the mapping logic to overlay those GeoJSON features onto your map, and shows you the diff. You get a working map component in minutes.

Automate Elevation and Oblique Views

Building 3D property views requires specific angles and topographic data. Cline can fetch a `get_dsm_elevation_tile` to extract pixelated surface models and map terrain heights directly into your application state. For structural analysis, it pulls a `get_oblique_tile` to give you North, South, East, or West perspectives. Cline writes the exact API wrapper code needed to cycle through these angles in your frontend.

Verify Coverage Before Coding (MCP Server)

Hardcoding coordinates that lack imagery coverage breaks apps. This MCP Server lets your agent run a `check_coverage_point` or `check_coverage_polygon` before it writes any fetch logic. If the data exists, Cline uses `list_survey_dates` to find the chronological availability. It then pulls the exact `get_survey_metadata` to ensure the optical flight details match your required resolution.

Setup guide

Set up Nearmap (High-Res Aerial Imagery & AI) MCP in Cline

Prerequisites

VS Code with Cline extension installed
Active Vinkius subscription with a valid endpoint token

1

Open Cline MCP settings

Click the Cline icon in the VS Code sidebar to open the Cline panel. Then click the MCP Servers icon (server stack) at the top-right corner of the panel.
2

Add a remote server

Click "Remote Servers" at the top, then click "Add Remote MCP". In the Name field, type nearmap-high-res-aerial-imagery-ai-mcp. In the URL field, paste your Vinkius endpoint: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp. Get your token from cloud.vinkius.com.
3

Enable the server

After saving, the server appears in the Cline MCP panel. Toggle the switch to enable it. The status indicator turns green when the connection is live.
4

Start using tools

Return to the Cline chat and ask: "Check my latest Nearmap (High-Res Aerial Imagery & AI) refund status." Cline will discover the available tools and request your approval before invoking each one — giving you full control over every action.

Cline MCP Settings

{
  "mcpServers": {
    "nearmap-high-res-aerial-imagery-ai-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about Nearmap (High-Res Aerial Imagery & AI) MCP in Cline

Open the Cline sidebar and click the MCP Servers icon. You can add it via the Remote Servers tab using the Streamable HTTP transport URL, or edit your cline_mcp_settings.json directly.

That is exactly what it does. You ask for a map viewer, and Cline uses `get_true_ortho_tile` to pull the lean-corrected imagery, then writes the HTML canvas or React code to display it.

Yes. Your agent can call `list_ai_feature_classes` to see the available computer vision categories. It then uses that taxonomy to extract specific roof arrays and solar panels.

Cline is smart enough to check first. It runs `check_coverage_polygon` to verify aerial survey boundaries. If a region is missing, it will tell you before attempting to write the integration code.

The endpoint operates on a strict zero-trust model. When your VS Code environment requests specific polygon boundaries and elevation tiles, the payload is processed in a temporary, isolated sandbox that terminates immediately after returning the data.

Use it with your favorite AI tools

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