OXII Smart Home MCP Server
Enables control of OXII smart home devices through the Model Context Protocol, supporting device switching, air conditioner control, cronjobs, and room scenarios. Integrates with chatbots and MCP-compatible clients for natural language home automation.
README
OXII Smart Home MCP Server
Modern documentation for the device-control MCP stack that pairs with the FastAPI chatbot. Use this guide the same way you would the chatbot docs: it covers setup, commands, tooling, and troubleshooting for standalone MCP development.
🔎 Overview
| Purpose | Expose OXII smart home controls (device info, switching, AC, cronjobs, one-touch, room scenarios) via the Model Context Protocol (MCP). |
| Transport | Server Sent Events (SSE) on port 9031. |
| Runtime | Python 3.10+, mcp.server.FastMCP with LangChain MCP adapters. |
| Consumers | The FastAPI chatbot (chatbot/) or any MCP-compatible client. |
mcp/oxii-server/
├── main.py # Boots the FastMCP process and registers tools
├── tools/ # Tool implementations (auth, device control, cronjobs…)
├── client.py # Quick demo client for manual testing
├── docker-compose.yml # Containerized runtime (exposes :9031)
└── .env.example # Sample environment for OXII credentials
✅ Prerequisites
- Python 3.10 or newer (Poetry will manage dependencies), or Docker Engine 20.10+
- OXII account credentials with device access (phone, password, country)
- Network access to the OXII staging/prod API defined in
OXII_BASE_URL
⚙️ Environment configuration
Create a working copy of the environment file and fill in the secrets:
cp .env.example .env
| Variable | Description |
|---|---|
OXII_BASE_URL |
Root URL for the OXII API (staging provided by default). |
OXII_PHONE / OXII_PASSWORD / OXII_COUNTRY |
Login used to obtain access tokens. |
PORT / HOST |
Optional overrides for where the MCP server listens (default 0.0.0.0:9031). |
DEBUG |
Toggle verbose logging (true/false). |
🚀 Running the server
Option 1 – Local Poetry workflow
poetry install
poetry run python main.py
This starts the server at http://localhost:9031/sse.
Option 2 – Docker Compose
cp .env.example .env # if you have not already
docker compose up --build -d
The compose stack exposes port 9031 on the host. Combine this with the chatbot by pointing OXII_MCP_SERVER_URL to http://host.docker.internal:9031/sse inside the chatbot container.
✅ Verifying the service
1. Use the bundled client
poetry run python client.py
Select a tool from the prompt and provide the required parameters to confirm end-to-end connectivity.
2. Visit the built-in docs UI
- Human friendly docs:
http://host.docker.internal:9031/docx - Machine readable catalogue:
http://host.docker.internal:9031/docs.json
3. Curl the SSE handshake
curl -N http://localhost:9031/sse
You should see an initial JSON payload describing the MCP capabilities.
🧰 Tool catalogue
Below is a quick reference for each registered MCP tool. All payloads are JSON structures passed through the MCP protocol.
| Tool | Purpose | Key parameters |
|---|---|---|
get_device_list |
List homes, rooms, devices, and remote buttons. | token |
switch_device_control |
Toggle SH1/SH2 relay devices. | token, house_id, device_id, button_code, command (ON/OFF) |
control_air_conditioner |
Full AC control (mode, temp, fan). | token, serial_number, mode, fan_speed, temperature, etc. |
create_device_cronjob |
Add/update/remove cronjobs for switches or AC. | token, device_id or button_id, action, cron_expression, command |
one_touch_control_all_devices |
Execute a house-wide preset (e.g., “turn everything off”). | token, house_id, status |
one_touch_control_by_type |
Toggle devices by type (LIGHT, CONDITIONER, …). | token, house_id, device_type, status |
room_one_touch_control |
Run a single-room preset. | token, room_id, status |
ℹ️ Detailed schemas live in
tools/next to each function. Review those modules for argument validation and API payload shapes.
🔄 Working with the chatbot
- Start the MCP server (local or Docker) and ensure port
9031is reachable from the chatbot environment. - In
chatbot/.env, setOXII_MCP_SERVER_URL=http://host.docker.internal:9031/ssewhen running the chatbot in Docker. - Restart the chatbot container (
docker compose restart app) to apply env changes. - Use the chatbot endpoint
POST /ai/agent-oxiiwith a valid OXII token—the agent will automatically call the MCP tools.
🧪 Testing & diagnostics
- Unit checks – Run
poetry run pytestif you add tests (seed filetest_tools.pyis available as a template). - Token validation – Use
chatbot/test_folders/testing_api.pyto fetch a fresh token before invoking tools. - Logs – With
DEBUG=true, the server prints detailed traces for each MCP call. In Docker, view them withdocker compose logs -f oxii-server.
🛠 Troubleshooting
| Symptom | Suggested fix |
|---|---|
httpx.ConnectError: All connection attempts failed |
The consumer is pointing to localhost from inside Docker. Use host.docker.internal or run both services on the same Compose network. |
| Authentication failures | Double-check OXII_PHONE, OXII_PASSWORD, and OXII_COUNTRY. Tokens expire—fetch a new one if requests start returning 401. |
| Cronjob payload rejected | Ensure the cron expression has 6 fields (second minute hour day month weekday) and matches the device type (SH1/SH2 vs SH4). |
| AC commands ignored | Some devices require numeric mode/fan values. See constants in tools/ac_control.py for valid ranges. |
| Docker rebuilds are slow | Use docker compose build oxii-server --no-cache after dependency changes, otherwise rely on cached layers. |
📚 Further reading
- Model Context Protocol (MCP) specification
- LangChain MCP Adapters
chatbot/README.mdfor the FastAPI-side integration guide.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.