pCloudy-mcp 0.1.3

MCP server for pCloudy

pCloudy-MCP

🔌 What is MCP?

MCP (Modular Context Protocol) is an open standard that simplifies how applications interact with large language models (LLMs). It's like a USB-C port for AI — a single, consistent way to connect tools and data sources to your LLMs.

MCP allows you to:

• 🔌 Plug LLMs into existing tools and APIs with ease
• 🔄 Switch between different LLM vendors with minimal effort
• 🔐 Keep data secure by executing within your infrastructure
• ⚙️ Build composable, modular workflows for real-world use cases

📖 Learn more about MCP →

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📱 About pCloudy-MCP

pCloudy-MCP serves as an MCP server that interacts with the pCloudy Device Cloud to:

• 📊 Manage test cases via natural language
• 📲 Execute manual or scripted tests on Android/iOS devices
• 🤖 Automate test steps using QPilot, an LLM-compatible AI testing agent

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🧠 Why Use It?

✅ Test from Anywhere

Easily control real devices using natural prompts — whether you're in a terminal, IDE, Claude, Cursor, or any other AI tool.

✅ Reduce Context Switching

Trigger device actions, upload builds, or run flows directly from your development or chat environment — no more jumping between tools.

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🧪 Examples

Manual Testing (Natural Language)

Use plain English to test your apps across real devices:

Upload the APK to the cloud
Install the app on a Pixel 6
Resign and upload the iOS build

🤖 QPilot Automation

Run intelligent automation steps with natural language:

Book another iOS device and run the following:
  - Enter username '[e-mail]'
  - Enter password 'pass'
  - Click on login

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✅ How to Use

🔧 Prerequisites

1. Sign up for pCloudy account 👉 pCloudy Sign Up

2. Install Python ≥ 3.10 on your machine

3. Install uv

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⚙️ Configuration (MCP-compatible tools)

To launch the pCloudy MCP server, use this configuration:

1. For claude claude_desktop_config.json

{
  "mcpServers": {
    "pCloudy": {
      "command": "uvx",
      "args": ["pcloudy-mcp"],
      "env": {
        "PCLOUDY_USERNAME": "<your_pcloudy_username>",
        "PCLOUDY_API_KEY": "<your_pcloudy_api_key>",
        "PCLOUDY_CLOUD_URL": "<your_pcloudy_cloud_url>"
      }
    }
  }
}

1. For cursor mcp.json

{
  "mcpServers": {
    "pCloudy": {
      "command": "uvx",
      "args": ["pcloudy-mcp"],
      "env": {
        "PCLOUDY_USERNAME": "<your_pcloudy_username>",
        "PCLOUDY_API_KEY": "<your_pcloudy_api_key>",
        "PCLOUDY_CLOUD_URL": "<your_pcloudy_cloud_url>"
      }
    }
  }
}

Replace the values with your actual credentials and endpoint.

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💠 Development

To work with this repo locally:

git clone https://github.com/Smart-Software-Testing-Solutions-Opkey/pcloudy-mcp-server.git

cd pcloudy-mcp-server

uv pip install .[dev]

Use the following poethepoet tasks:

poe format         # black + isort
poe lint-check     # ruff linter
poe typecheck      # mypy type checks
poe check-server   # check server is working or not

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📁 Project Structure

src/
└── pcloudy_mcp/
    ├── main.py          # CLI entry point
    ├── server.py        # FastMCP app factory
    ├── api/             # API logic (auth, booking, etc.)
    ├── utils/           # Configuration 
	|── tools/           # Tools setup
	├── logger/          # logging
    ├── Constants/       # constants
	├── errors/          # Handle Errors and Exceptions
	└── validation/      # Env Validation

👥 Contributors

Maintained by the pCloudy team.