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HiveFlow MCP Server

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# @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 ```bash npm install -g @hiveflow/mcp-server ``` ### Configuration Add to your MCP client configuration (e.g., `.cursor/mcp.json`): ```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 ```json { "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) ```bash 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 ```bash 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: ```bash export DEBUG=hiveflow-mcp:* ``` ## 📚 Documentation - [HiveFlow Documentation](https://doc.hiveflow.ai) - [MCP Protocol Specification](https://modelcontextprotocol.io) - [API Reference](https://api.hiveflow.ai/docs) ## 🤝 Contributing We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details. ## 📄 License MIT License - see [LICENSE](LICENSE) file for details. ## 🆘 Support - [GitHub Issues](https://github.com/hiveflowai/hiveflow-mcp-server/issues) - [Discord Community](https://discord.gg/3cc69VFb) - [Email Support](mailto:support@hiveflow.ai) --- Made with ❤️ by the HiveFlow team

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