Hi everyone!
I’ve been really excited to see CesiumGS’s official work on cesium-ai-integrations — it’s great to see MCP support coming to the Cesium ecosystem.
Inspired by that direction, I’d like to share a community project I’ve been working on: cesium-mcp. It’s an open-source MCP server that lets AI assistants (Claude, Copilot, Cursor, etc.) interact with a CesiumJS Viewer through natural language.
What it does
cesium-mcp provides a browser-side SDK (cesium-mcp-bridge) that connects to a Node.js MCP server (cesium-mcp-runtime) via WebSocket. This allows AI agents to execute CesiumJS operations like:
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Camera navigation (flyTo, setView, orbit)
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Adding entities (markers, polygons, models, labels, and more)
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Managing layers (GeoJSON, 3D Tiles, imagery services)
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Creating trajectory animations
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Taking screenshots
Currently it has 43 tools organized in 10 groups, with a dynamic discovery mechanism so the AI can activate tool groups on demand.
How it relates to the official project
cesium-mcp started independently before the official cesium-ai-integrations was announced. Since then, I’ve been aligning the tool design with the official approach — the camera, entity, and animation features follow similar patterns to the official servers.
I see this as complementary to the official effort — exploring additional use cases like layer management, GeoJSON loading, and remote deployment (via Streamable HTTP) that might be useful for the community. I also submitted a feature request (Issue #19) with some ideas for the official project.
Quick start
# In your CesiumJS project
npm install cesium-mcp-bridge
# In your app code
const bridge = new CesiumMcpBridge(viewer, { port: 9100 });
bridge.connect();
# Start the MCP server
npx cesium-mcp-runtime
Links
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Documentation: Cesium MCP
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npm: cesium-mcp-bridge / cesium-mcp-runtime / cesium-mcp-dev
I’d love to hear any feedback or suggestions from the community. Especially interested in what use cases you’d find most valuable for AI + CesiumJS integration.
Thanks!