semvec/pypi-packages huggingface dataset:
actionai-mcp 1.0.0
ActionAI MCP HTTP client for Claude Desktop and other MCP-compatible applications
Requires Python: >=3.8
Keywords: actionai, ai, assistant, claude, mcp, model-context-protocol

# ActionAI MCP Python Client

ActionAI MCP HTTP client for Claude Desktop and other MCP-compatible applications.

## Installation

### Using uvx (Recommended)

```bash
# Test connection
uvx actionai-mcp --test

# Use with environment variables
MCP_SERVER_URL=http://localhost:8089/mcp ACTIONAI_API_KEY=client-access-key-2024 uvx actionai-mcp --test
```

### Using pip

```bash
pip install actionai-mcp
actionai-mcp --test
```

## Configuration

### Environment Variables

- `MCP_SERVER_URL`: URL of the ActionAI MCP HTTP service (default: `http://localhost:8089/mcp`)
- `MCP_TIMEOUT`: Request timeout in seconds (default: `30`)
- `ACTIONAI_API_KEY`: API key for ActionAI service authentication (default: `client-access-key-2024`)

### Claude Desktop Configuration

Add this to your Claude Desktop MCP configuration:

```json
{
  "mcpServers": {
    "actionai-mcp": {
      "command": "uvx",
      "args": ["actionai-mcp"],
      "env": {
        "MCP_SERVER_URL": "http://localhost:8089/mcp",
        "ACTIONAI_API_KEY": "client-access-key-2024"
      }
    }
  }
}
```

### Augment Code Configuration

Add this to your Augment Code MCP configuration:

```json
{
  "mcpServers": {
    "actionai-mcp": {
      "command": "uvx",
      "args": ["actionai-mcp"],
      "env": {
        "MCP_SERVER_URL": "http://localhost:8089/mcp",
        "ACTIONAI_API_KEY": "client-access-key-2024"
      }
    }
  }
}
```

### Cursor Configuration

Add this to your Cursor MCP configuration:

```json
{
  "mcpServers": {
    "actionai-mcp": {
      "command": "uvx",
      "args": ["actionai-mcp"],
      "env": {
        "MCP_SERVER_URL": "http://localhost:8089/mcp",
        "ACTIONAI_API_KEY": "client-access-key-2024"
      }
    }
  }
}
```

## Usage

### Test Connection

```bash
# Test with default settings
uvx actionai-mcp --test

# Test with custom URL
uvx actionai-mcp http://localhost:8089/mcp --test

# Test with environment variables
MCP_SERVER_URL=http://localhost:8089/mcp uvx actionai-mcp --test
```

### Command Line Options

```bash
uvx actionai-mcp --help
```

Options:
- `--test, -t`: Test connection to MCP server
- `--version, -v`: Show version information
- `--help, -h`: Show help message

## Development

### Local Development

```bash
# Clone the repository
git clone https://github.com/your-org/actionai-mcp-client.git
cd actionai-mcp-client/mcp/python-package

# Install in development mode
pip install -e .

# Test
actionai-mcp --test
```

### Publishing

```bash
# Build the package
python -m build

# Upload to PyPI
python -m twine upload dist/*
```

## License

MIT License - see LICENSE file for details.
dataprovider-sdk 1.0.0
A lightweight SDK for interacting with the Dataprovider.com API.
Requires Python: >=3.13

# Dataprovider.com Python SDK

A lightweight SDK for interacting with the [Dataprovider.com](https://www.dataprovider.com) API in Python.\
This client provides a convenient way to authenticate, build requests, and handle responses for GET, POST, and PUT operations.

## 🚀 Installation

Use [PIP](https://pypi.org/project/pip/) to install the SDK:

```bash
pip install dataprovider-sdk
```

## ✅ Requirements

- Python >= 3.13
- PIP for dependency management

## 🔧 Usage

```python
from requests.exceptions import HTTPError
from dataprovider.sdk.client.api_client import ApiClient

def main():
    client = ApiClient('username', 'password')

    try:
        response = client.get(path='/datasets/list')
    except HTTPError as e:
        print(f'An error occurred ({e.response.status_code}): {e.response.text}')
        return

    # Access the response data as text
    print(response.text)

    # Access the response data as dict
    print(response.json())

if __name__ == '__main__':
    main()
```

See [examples](examples) for more.