SenseCAP PaaS MCP Bridge - 1

SenseCAP PaaS MCP Bridge

Give any MCP-compatible voice assistant or LLM a spoken, anomaly-first report on your SenseCAP PaaS device fleet — ask "how are my devices doing" or "what's the greenhouse reading right now" and get a real answer, no app or dashboard needed.

Beginner10minVoice AI
MCPvoice-aisensecappaasxiaozhidocker

What This Capability Does

Gives any MCP-compatible voice assistant or LLM a live, spoken-language connection to your SenseCAP PaaS device fleet. Ask "how are my devices doing" and get an anomaly-first fleet report, or ask about one device by name for its full current reading — no app, no dashboard, no query language. Device registration and key lookup are also available for setup workflows.

What You Get After Deploying

  • A farm overview tool: ask "how are my devices doing" and get one spoken answer — how many devices, who's offline, whose battery is low, presented anomaly-first so a healthy fleet doesn't waste your time.
  • A device reading tool: ask about one device by name and get every channel's current reading spoken in plain language (temperature, humidity, soil moisture, wind, rainfall, and more), not raw numbers.
  • A device registry tool: register a new SenseCAP device and get back its EUI, by name.
  • A device key lookup tool: get a device's device_key/token by name or EUI — used when provisioning firmware.
  • A live telemetry tool: ask for the latest reading from any device by name or EUI — returns the newest data point for every channel it reports, not just one value.
  • A history tool: pull historical telemetry for a time range, plus a chart-ready aggregation tool for plotting trends.
  • A code-template tool: list and read Arduino/PlatformIO templates for reporting sensor data and device status to SenseCAP.
  • The farm overview and device reading tools speak a complete, ready-to-hear sentence built from real numbers. The telemetry/history/chart/key tools return a short summary plus the full structured data instead — built for scripting and follow-up processing, not meant to be read aloud verbatim.

What You Can Connect It To

  • XiaoZhi (小智) voice assistants — the primary target: point it at your XiaoZhi MCP access point and ask about your devices out loud.
  • Any other MCP-compatible host — Claude Desktop, Cursor, or a custom LLM agent that speaks the Model Context Protocol.

Interface for Your Program

InterfaceWhat it doesHow to connectData format
MCP over WebSocketOutbound connection to an MCP access point, exposing 9 toolsSet MCP_ENDPOINT to your access point URLJSON-RPC (MCP)

This container only dials out — it never listens on a port, so there's nothing to expose or firewall.

Usage Notes

  • You need a SenseCAP PaaS account with an Access ID/Key pair (sensecap.seeed.cc → API keys) and devices already reporting data to it.
  • You need a XiaoZhi MCP access point URL (from your XiaoZhi console) if you're connecting it to a XiaoZhi voice assistant.
  • Credentials are entered at deploy time only and are never baked into the Docker image — update them any time by redeploying this preset with new values.

Integration Interfaces

websocket

Outbound MCP (Model Context Protocol) JSON-RPC bridge. Dials out to a XiaoZhi voice-assistant MCP access point (or any MCP-compatible host) and exposes 9 tools — get_farm_overview, get_device_reading, register_device, get_device_key, view_latest_telemetry_data, list_telemetry_data, aggregate_chart_points, list_all_code, read_code_file.

{"method":"tools/call","params":{"name":"get_farm_overview","arguments":{}}}

Deployment Options

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