Flightradar24 MCP Server for Cloud Run

A lightweight, secure Dockerized proxy that allows the official Flightradar24 MCP Server to run as a remote HTTP service.

By default, the official FR24 server operates over stdio (Standard Input/Output), which requires the server to be run locally by the client. This repository wraps the server using mcp-proxy to expose it over Server-Sent Events (SSE) and Streamable HTTP. This allows it to be deployed to container hosting platforms like Google Cloud Run and accessed remotely by any MCP-compatible AI agent.

Features

• Client-Provided API Keys: The server acts as a stateless passthrough. It does not store your FR24 API key; instead, clients must provide their own API key via HTTP headers.
• Distroless Container: Built on a Debian 12 distroless Node.js image to vastly reduce the attack surface.
• Cloud Run Ready: Honors the $PORT environment variable and binds gracefully, intercepting SIGTERM for proper shutdown.

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🛠 Building & Running Locally

1. Build the Docker Image

docker build -t fr24-mcp-cloudrun .

2. Run the Container

You don't need to pass the API key to the container. It will listen on port 8080.

docker run -d -p 8080:8080 --name fr24-server fr24-mcp-cloudrun

3. Test the Endpoint

You can verify the connection by passing your API key via the FR24-API-KEY header:

curl -v -H "FR24-API-KEY: YOUR_FR24_API_KEY" http://localhost:8080/sse

---

🚀 Deploying to Google Cloud Run

You can deploy this directly to Cloud Run using the Google Cloud CLI:

gcloud run deploy fr24-mcp-server 
  --source . 
  --region us-central1 
  --allow-unauthenticated 
  --port 8080

Note down the resulting URL (e.g., https://fr24-mcp-server-hash.a.run.app). Your SSE endpoint will be this URL with /sse appended.

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🔌 Connecting Clients (Gemini CLI & ADK Agents)

Because this server operates over HTTP/SSE rather than stdio, you must configure your MCP client (like Gemini CLI or ADK Agent) to use an SSE Transport and pass your Flightradar24 API key via headers.

Gemini CLI Configuration

In your Gemini CLI workspace or global configuration (usually located in .gemini/mcp.json or your MCP registry), add the server as an SSE connection. You must provide the FR24-API-KEY header.

{
  "mcpServers": {
    "flightradar24": {
      "type": "sse",
      "url": "https://YOUR_CLOUDRUN_URL/sse",
      "headers": {
        "FR24-API-KEY": "YOUR_FR24_API_KEY"
      }
    }
  }
}

(If running locally, replace url with http://localhost:8080/sse)

ADK Agent Configuration

If you are building an agent using a standard Model Context Protocol (MCP) TypeScript or Python client SDK, initialize the client using the SSE transport and provide the authorization header:

TypeScript / Node.js:

import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { SSEClientTransport } from "@modelcontextprotocol/sdk/client/sse.js";

const transport = new SSEClientTransport(
  new URL("https://YOUR_CLOUDRUN_URL/sse"), 
  {
    headers: {
      "FR24-API-KEY": "YOUR_FR24_API_KEY"
      // Alternatively, use "Authorization": "Bearer YOUR_FR24_API_KEY"
    }
  }
);

const client = new Client(
  { name: "adk-agent-client", version: "1.0.0" },
  { capabilities: { tools: {} } }
);

await client.connect(transport);
console.log("Connected to Flightradar24 remote MCP!");

Python:

import asyncio
from mcp import ClientSession
from mcp.client.sse import sse_client

async def main():
    url = "https://YOUR_CLOUDRUN_URL/sse"
    headers = {"FR24-API-KEY": "YOUR_FR24_API_KEY"}
    
    async with sse_client(url, headers=headers) as streams:
        async with ClientSession(streams[0], streams[1]) as session:
            await session.initialize()
            
            # Fetch available tools
            tools = await session.list_tools()
            print("Available FR24 Tools:", tools)

asyncio.run(main())