Fledge MCP Server

Name: Fledge MCP Server
Author: Krupalp525

@Krupalp525

Repository

About Fledge MCP Server

Fledge Model Context Protocol (MCP) Server for Cursor AI integration

#fledge #mcp #cursor-ai

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "fledge-mcp": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "fledge-mcp",
        "."
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Fledge MCP Server?

A Model Context Protocol (MCP) server that connects Fledge functionality to Cursor AI, allowing the AI to interact with Fledge instances via natural language commands. It requires Fledge installed locally or accessible via API (default: http://localhost:8081).

How to use Fledge MCP Server?

Install dependencies with pip install -r requirements.txt, ensure Fledge is running (fledge start), then launch the server with python mcp_server.py or python secure_mcp_server.py for API‑key authentication. In Cursor AI, add an MCP server with URL http://localhost:8082/tools and optionally the X-API-Key header. Test by typing “Check if Fledge API is reachable” in Cursor’s Composer.

Key features of Fledge MCP Server

Exposes 16 tools for data access, service control, and UI generation
Supports secure API key authentication via secure_mcp_server.py
Implements JSON-RPC 2.0 over WebSocket transport
Generates React components for Fledge data visualization
Enables real-time sensor data subscriptions and latest readings
Can be deployed on Smithery.ai for enhanced scalability

Use cases of Fledge MCP Server

Validate Fledge API connectivity using natural language commands
Fetch and filter sensor data for analysis or visualization
Generate mock sensor data for testing and development
Start or stop Fledge services via Cursor AI commands
Create frontend UI components for Fledge dashboards

FAQ from Fledge MCP Server

What are the prerequisites?

Fledge installed locally or accessible via API, Cursor AI, and Python 3.8+.

How does secure mode work?

Run python secure_mcp_server.py. It generates an API key stored in api_key.txt. All requests must include the X-API-Key header; the health endpoint remains unauthenticated.

What transport does the server use?

The server uses WebSocket transport and the Model Context Protocol implemented via JSON-RPC 2.0.

Can it be deployed to the cloud?

Yes, it can be deployed on Smithery.ai using Docker and the smithery CLI, with configurable environment variables for the Fledge API URL and API key.