Fledge IoT
Summary
Fledge MCP Server provides a bridge between Fledge IoT platform and AI assistants, enabling natural language interaction with sensor data and system management. Developed by Krupal Patel, it offers tools for data access, service control, UI component generation, and real-time streaming over WebSockets. The implementation includes both standard and secure API key authentication modes, with Docker containerization for easy deployment on Smithery.ai. This server is particularly valuable for IoT workflows requiring data visualization, monitoring, and configuration management without leaving the conversation interface.
Available Actions(16)
get_sensor_data
Fetch sensor data from Fledge with optional filtering by time range and limit.
list_sensors
List all sensors available in Fledge.
ingest_test_data
Ingest test data into Fledge, with optional batch count.
get_service_status
Get the status of all Fledge services.
start_stop_service
Start or stop a Fledge service by type.
update_config
Update Fledge configuration parameters.
generate_ui_component
Generate React components for Fledge data visualization.
fetch_sample_frontend
Get sample frontend templates for different frameworks.
suggest_ui_improvements
Get AI-powered suggestions for improving UI code.
subscribe_to_sensor
Set up a subscription to sensor data updates.
get_latest_reading
Get the most recent reading from a specific sensor.
validate_api_connection
Check if the Fledge API is reachable.
simulate_frontend_request
Test API requests with different methods and payloads.
get_api_schema
Get information about available Fledge API endpoints.
list_plugins
List available Fledge plugins.
generate_mock_data
Generate realistic mock sensor data for testing.
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