Give your AI agent eyes on the physical world — an MCP server for real-time DePIN edge-vision queries.
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# mcp-spatial-perception [](https://github.com/jamie643/mcp-spatial-perception/actions/workflows/ci.yml) [](https://github.com/jamie643/mcp-spatial-perception/actions/workflows/publish.yml) [](https://pypi.org/project/mcp-spatial-perception/) [](https://pypi.org/project/mcp-spatial-perception/) [](https://opensource.org/licenses/MIT) [](https://github.com/astral-sh/ruff) > **Give your AI agent eyes on the physical world.** > > An [MCP](https://modelcontextprotocol.io) server that exposes real-time spatial perception queries from DePIN edge-vision nodes to any LLM that speaks the Model Context Protocol — Claude Desktop, Cursor, Claude Code, or a custom agent framework. --- ## The problem LLM agents can read files, browse the web, and call APIs — but they're blind to the physical world. They can't answer questions like: - *"Is there foot traffic at location X right now?"* - *"What is the live visual state of camera node #402?"* - *"Is the loading dock clear before I dispatch the truck?"* There's no standard way for an agent to ask those questions. ## The solution `mcp-spatial-perception` is a small, dependency-free MCP server that sits between your agent and a DePIN network of edge-vision nodes. The agent calls a tool, the server queries the network, and structured JSON describing the scene comes back — detections, bounding boxes, confidence scores, environmental state, geolocation. ``` ┌─────────────┐ MC…
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