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Fledge IoT

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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

Last Updated: April 25, 2025

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