MCP Test Scratch Server

MCP Test Scratch Server

A Flask-based MCP server designed for testing deployment on Google App Engine. Provides a deeplink checking endpoint that accepts flattened JSON parameters and forwards them as nested objects to external APIs.

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README

MCP Server Deployment on Google App Engine This document provides step-by-step instructions to deploy the provided MCP server on Google App Engine.

Files The following files are required for deployment:

main.py: The Python Flask application code.

requirements.txt: A list of Python libraries the server needs.

app.yaml: The configuration file for Google App Engine.

Prerequisites Google Cloud Account: You need an active Google Cloud account with billing enabled.

Google Cloud SDK: Install the Google Cloud SDK on your local machine.

Python: Python 3.9 or newer should be installed.

Text Editor: Any text editor to create and save the files above.

Step 1: Set up your Google Cloud Project Create a new Google Cloud Project or select an existing one.

Open a terminal or command prompt.

Authenticate your Google Cloud SDK by running:

gcloud auth login

Set your project ID:

gcloud config set project YOUR_PROJECT_ID

(Replace YOUR_PROJECT_ID with your actual project ID).

Enable the App Engine Admin API for your project.

Step 2: Create the Files Ensure the three files (main.py, requirements.txt, and app.yaml) are saved in the same directory on your computer.

Step 3: Deploy to Google App Engine Open your terminal and navigate to the directory where you saved the files.

Run the following command to deploy your application:

gcloud app deploy

You will be prompted to choose a region and confirm the deployment. Type Y and press Enter. The deployment process may take a few minutes.

Step 4: Test the Deployed Server Once the deployment is complete, Google Cloud will provide you with a URL for your service, typically in the format https://YOUR_PROJECT_ID.REGION_ID.r.appspot.com.

You can test the endpoint using a curl command from your terminal. This command mimics the request that Intercom will send, with the flattened JSON parameters.

curl --location 'https://YOUR_PROJECT_ID.REGION_ID.r.appspot.com/v2/iw/check-deeplink'
--header 'Content-Type: application/json'
--data '{ "db_name": "NDTVProfit", "user_id": "eb50c9bb-fac4-44c7-b97d-36ab374c5ef8", "campaign_id": "68b2cd88c85096a0c1603cf0", "date": "2025-08-30", "region":"DC1" }'

Remember to replace YOUR_PROJECT_ID and REGION_ID with your specific values. The server should return the expected JSON response from the external API.

This setup ensures that your server is ready to integrate with Intercom, accepting the required flattened schema and forwarding the request as a nested object to the final API endpoint.

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