HiveFlow MCP Server

HiveFlow MCP Server

Connects AI assistants (Claude, Cursor, etc.) directly to the HiveFlow automation platform, allowing them to create, manage, and execute automation flows through natural language commands.

Category
访问服务器

Tools

create_flow

Crea un nuevo flujo de trabajo en HiveFlow

list_flows

Lista todos los flujos de trabajo del usuario

get_flow

Obtiene detalles de un flujo específico

execute_flow

Ejecuta un flujo de trabajo específico

pause_flow

Pausa un flujo activo

resume_flow

Reanuda un flujo pausado

list_mcp_servers

Lista los servidores MCP configurados en HiveFlow

create_mcp_server

Registra un nuevo servidor MCP en HiveFlow

get_flow_executions

Obtiene el historial de ejecuciones de un flujo

README

@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 Contributing Guide for details.

📄 License

MIT License - see LICENSE file for details.

🆘 Support


Made with ❤️ by the HiveFlow team

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