hiveflow-mcp-server

hiveflow-mcp-server

3.2

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The @hiveflow/mcp-server is the official Model Context Protocol (MCP) server for HiveFlow, enabling seamless integration of AI assistants with the HiveFlow automation platform.

@hiveflow/mcp-server

Official Model Context Protocol (MCP) server for HiveFlow. Connect your AI assistants (Claude, Cursor, etc.) directly to your HiveFlow automation platform.

🚀 Quick Start

Installation

npm install -g @hiveflow/mcp-server

Configuration

Add to your MCP client configuration (e.g., .cursor/mcp.json):

{
  "mcpServers": {
    "hiveflow": {
      "command": "npx",
      "args": ["-y", "@hiveflow/mcp-server"],
      "env": {
        "HIVEFLOW_API_KEY": "your-api-key-here",
        "HIVEFLOW_API_URL": "https://api.hiveflow.ai"
      }
    }
  }
}

For Local Development

{
  "mcpServers": {
    "hiveflow": {
      "command": "npx",
      "args": ["-y", "@hiveflow/mcp-server"],
      "env": {
        "HIVEFLOW_API_KEY": "your-api-key-here",
        "HIVEFLOW_API_URL": "http://localhost:5000"
      }
    }
  }
}

🔑 Getting Your API Key

Option 1: From HiveFlow Dashboard

  1. Log in to your HiveFlow dashboard
  2. Go to Settings > API Keys
  3. Generate a new API key

Option 2: From Command Line (Self-hosted)

cd your-hiveflow-backend
node get-api-key.js your-email@example.com

🛠️ Available Tools

Once configured, you'll have access to these tools in your AI assistant:

Flow Management

  • create_flow - Create new automation flows
  • list_flows - List all your flows
  • get_flow - Get details of a specific flow
  • execute_flow - Execute a flow with optional inputs
  • pause_flow - Pause an active flow
  • resume_flow - Resume a paused flow
  • get_flow_executions - Get execution history

MCP Server Management

  • list_mcp_servers - List configured MCP servers
  • create_mcp_server - Register new MCP servers

📊 Available Resources

  • hiveflow://flows - Access to all your flows data
  • hiveflow://mcp-servers - MCP servers configuration
  • hiveflow://executions - Flow execution history

💡 Usage Examples

Create a New Flow

AI: "Create a flow called 'Email Processor' that analyzes incoming emails"

List Active Flows

AI: "Show me all my active flows"

Execute a Flow

AI: "Execute the flow with ID 'abc123' with input data {email: 'test@example.com'}"

Get Flow Status

AI: "What's the status of my Email Processor flow?"

🔧 Configuration Options

Environment Variables

  • HIVEFLOW_API_KEY - Your HiveFlow API key (required)
  • HIVEFLOW_API_URL - Your HiveFlow instance URL (default: https://api.hiveflow.ai)
  • HIVEFLOW_INSTANCE_ID - Instance ID for multi-tenant setups (optional)

Command Line Options

hiveflow-mcp --api-key YOUR_KEY --api-url https://your-instance.com

🏗️ Architecture

This MCP server acts as a bridge between your AI assistant and HiveFlow:

AI Assistant (Claude/Cursor) ↔ MCP Server ↔ HiveFlow API

🔒 Security

  • API keys are transmitted securely over HTTPS
  • All requests are authenticated and authorized
  • No data is stored locally by the MCP server

🐛 Troubleshooting

Common Issues

"HIVEFLOW_API_KEY is required"

  • Make sure you've set the API key in your MCP configuration
  • Verify the API key is valid and not expired

"Cannot connect to HiveFlow API"

  • Check that your HiveFlow instance is running
  • Verify the API URL is correct
  • Ensure there are no firewall restrictions

"MCP server not found"

  • Restart your AI assistant completely
  • Verify the MCP configuration file is in the correct location
  • Check that the package is installed: npm list -g @hiveflow/mcp-server

Debug Mode

For detailed logging, set the environment variable:

export DEBUG=hiveflow-mcp:*

📚 Documentation

🤝 Contributing

We welcome contributions! Please see our for details.

📄 License

MIT License - see file for details.

🆘 Support

Made with ❤️ by the HiveFlow team