claude mcp add esp-rainmaker-mcp -- npx -y esp-rainmaker-mcp
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
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18 โ ยท espressif/esp-rainmaker-mcp ยท read from the repository page ยท (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list ยท type: MCP server
Harvest history
first seen 2026-10-09 ยท last seen 2026-10-16 ยท seen 32ร ยท listed by 10 sources
Score
score 1,003 ยท 18 โ ยท 10 sources ยท mcp
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repository espressif/esp-rainmaker-mcp๏ผfirst catalogued 2026-10-09๏ผlast seen 2026-10-16ใThere is no official certification or quality rating here โ we record sources and dates only.
This project provides a Model Context Protocol (MCP) server wrapper around the esp-rainmaker-cli Python library. It allows MCP-compatible clients (like LLMs or applications such as Cursor, Claude Desktop, and Windsurf) to interact with your ESP RainMaker devices using the official CLI. Introduction to Model Context Protocol (MCP) The **Model Context Protocol (MCP)** is a standardized framework that enables AI systems to interact with external tools, data sources, and services in a unified manner. Introduced by Anthropic and adopted by major AI organizations, MCP acts as a universal interface, much like USB-C for hardware, allowing seamless integration across different platforms. Key Benefits of MCP in ESP RainMaker - **Unified Interaction**: MCP allows AI models to access and control IoT devices using natural language prompts, making interactions more intuitive and accessible. - **Real-time Control**: With MCP, users can execute actions such as turning devices on/off, adjusting settings, and managing schedules directly through AI interfaces. - **Local Server, Cloud-Backed Control**: The ESP RainMaker MCP server runs locally and stores credentials on your machine. However, device management actions are performed via the official ESP RainMaker cloud APIs through the esp-rainmaker-cli. By integrating MCP, the ESP RainMaker platform enhances its capabilities, allowing tools like Claude, Cursor, Windsurf, and Gemini CLI to manage IoT devices efficiently and securely. Prerequisites * **Python:** Version 3.10 or higher * **uv:** The uv Python package manager. Install from Astral's uv documentation. * **ESP RainMaker CLI Login:** You *must* have successfully logged into ESP RainMaker using the standard esp-rainmaker-cli login command in your terminal at least once. This server relies on the credentials saved by that process. * **RainMaker Nodes** added into your account since onboarding isn't supported by the MCP server. Installation & Setup 1. **Clone the Repository:** 2. **Install Dependencies using uv:** This command installs esp-rainmaker-cli, mcp[cli], and any other dependencies listed in pyproject.toml into a virtual environment managed by uv. *(This assumes uv is installed)* 3. **Login to ESP Rainmaker using esp-rainmaker-cli** > [!NOTE] > Direct login via username/password within MCP is not supported for security reasons. Please use the standard CLI login flow first. Client Configuration To add this project as an MCP server in supported MCP clients (Cursor, Claude Desktop, Windsurf, and Gemini CLI), you'll need to add the same JSON configuration to each client's config file. The configuration is identical across all clients: MCP Server Configuration (All Clients) Use the following JSON configuration for all MCP clients: > [!IMPORTANT] > Replace /server.py with the actual **absolute path** to the server.py file within the cloned esp-rainmaker-mcp directory on your system. Cursor MCP Server Setup 1. Open Cursor and click on the settings (gear icon) at the top right. 2. Navigate to "Tools & Integrations" from the settings menu. 3. Click on "MCP Tools" in the integrations section. 4. Click on "New MCP Server" to add a new server. 5. This will open the mcp.json file. Add the JSON configuration shown above. Claude Desktop MCP Server Setup 1. Open Claude Desktop and go to Settings -> Developer -> Edit Config. 2. This will open the configuration file (claude_desktop_config.json). Add the JSON configuration shown above. 3. Save the changes and restart Claude Desktop to apply the new settings.