🚀 Massive API MCP Server

A production-ready Model Context Protocol (MCP) server that provides real-time market data from Massive API for ChatGPT integration. Built specifically for the OPTION TRADER ChatGPT project.

📋 Overview

This MCP server exposes 5 powerful tools for accessing live market data:

1. get_stock_quote - Real-time stock quotes
2. get_options_chain - Options chain data with Greeks and IV
3. get_historical_bars - Historical OHLCV price data
4. get_market_snapshot - Comprehensive market snapshots
5. search_ticker - Search for ticker symbols

🎯 Features

• ✅ Built with FastMCP framework for optimal performance
• ✅ Async/await for concurrent requests
• ✅ Comprehensive error handling
• ✅ Detailed logging
• ✅ Production-ready deployment to Render.com
• ✅ Environment-based configuration
• ✅ Type hints and documentation
• ✅ ChatGPT Developer Mode compatible

📦 Prerequisites

• Python 3.10 or higher
• Massive API key (from trademassive.com)
• Render.com account (for deployment)
• ChatGPT Plus subscription with Developer Mode access

🛠️ Installation

Local Setup

1. Clone or navigate to the project directory:

   cd /home/ubuntu/massive-mcp-server

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\\Scripts\\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   cp .env.example .env

   Edit .env and add your Massive API key:

   MASSIVE_API_KEY=FbDpcHDdxr8qQAH0BQZToWkyxEqU9ead
   

5. Run the server locally:

   python server.py

🌐 Deployment to Render.com

Method 1: Using Render Dashboard (Recommended)

1. Push your code to GitHub:

   git init
   git add .
   git commit -m "Initial commit: Massive API MCP Server"
   git branch -M main
   git remote add origin https://github.com/YOUR_USERNAME/massive-mcp-server.git
   git push -u origin main

2. Create a new Web Service on Render:

   • Go to Render Dashboard
   • Click "New +" → "Web Service"
   • Connect your GitHub repository
   • Select the massive-mcp-server repository

3. Configure the service:

   • Name: massive-mcp-server
   • Region: Oregon (US West)
   • Branch: main
   • Runtime: Python 3
   • Build Command: pip install -r requirements.txt
   • Start Command: python server.py
   • Instance Type: Free

4. Add Environment Variables: In the "Environment" section, add:

   • Key: MASSIVE_API_KEY
   • Value: FbDpcHDdxr8qQAH0BQZToWkyxEqU9ead

5. Deploy:

   • Click "Create Web Service"
   • Wait for deployment to complete (usually 2-3 minutes)
   • Your server URL will be: https://massive-mcp-server.onrender.com

Method 2: Using render.yaml (Blueprint)

1. Push your code to GitHub (same as Method 1, step 1)

2. Create from Blueprint:

   • Go to Render Dashboard
   • Click "New +" → "Blueprint"
   • Connect your repository
   • Render will auto-detect render.yaml
   • Add the MASSIVE_API_KEY environment variable
   • Click "Apply"

🤖 Connecting to ChatGPT Developer Mode

Once deployed, connect your MCP server to ChatGPT:

Step 1: Get Your Server URL

After deployment on Render, your server URL will be:

https://massive-mcp-server.onrender.com

Step 2: Configure ChatGPT

1. Open ChatGPT Settings:

   • Go to ChatGPT
   • Click your profile → Settings
   • Navigate to Beta Features
   • Enable "Developer Mode"

2. Add MCP Server:

   • Go to "Customize ChatGPT" → "Create new GPT" or open your existing "OPTION TRADER" project
   • In the "Configure" tab, scroll to "Actions"
   • Click "Create new action"

3. Configure MCP Connection:

   • Server URL: https://massive-mcp-server.onrender.com
   • The server will automatically expose its tools via MCP protocol

Step 3: Test the Connection

In ChatGPT, try these test queries:

Get me a quote for AAPL

Show me the options chain for SPY expiring on 2026-02-20

Get historical daily bars for TSLA from 2026-01-01 to 2026-01-27

Search for Microsoft ticker

📚 Tool Documentation

1. get_stock_quote(symbol)

Get real-time stock quote.

Parameters:

• symbol (string, required): Stock ticker symbol (e.g., 'AAPL', 'TSLA', 'SPY')

Returns:

• Current price, bid/ask, volume, and other quote data

Example:

get_stock_quote('AAPL')
# Returns: {"symbol": "AAPL", "price": 192.50, "bid": 192.48, "ask": 192.52, ...}

2. get_options_chain(symbol, expiration)

Get options chain data.

Parameters:

• symbol (string, required): Stock ticker symbol
• expiration (string, optional): Expiration date in YYYY-MM-DD format

Returns:

• Options chain with calls/puts, strikes, Greeks, IV, volume, OI

Example:

get_options_chain('SPY', '2026-02-20')
# Returns full options chain for SPY expiring Feb 20, 2026

3. get_historical_bars(symbol, timeframe, from_date, to_date, limit)

Get historical OHLCV data.

Parameters:

• symbol (string, required): Stock ticker symbol
• timeframe (string, optional): Bar size - '1Min', '5Min', '15Min', '1H', '1D' (default: '1D')
• from_date (string, optional): Start date YYYY-MM-DD
• to_date (string, optional): End date YYYY-MM-DD
• limit (integer, optional): Max bars to return (default: 100, max: 10000)

Returns:

• Historical OHLCV bars with timestamps

Example:

get_historical_bars('AAPL', '1D', '2026-01-01', '2026-01-27')
# Returns daily bars for January 2026

4. get_market_snapshot(symbol)

Get comprehensive market snapshot.

Parameters:

• symbol (string, required): Stock ticker symbol

Returns:

• Quote, daily stats, trading statistics, market status

Example:

get_market_snapshot('TSLA')
# Returns comprehensive Tesla market data

5. search_ticker(query, limit)

Search for ticker symbols.

Parameters:

• query (string, required): Search term (company name or partial symbol)
• limit (integer, optional): Max results (default: 10)

Returns:

• List of matching symbols with names and exchanges

Example:

search_ticker('apple')
# Returns: [{"symbol": "AAPL", "name": "Apple Inc.", "exchange": "NASDAQ", ...}]

🔧 Configuration

Environment Variables

Variable	Description	Required	Default
MASSIVE_API_KEY	Your Massive API key	Yes	-
PORT	Server port	No	8000
HOST	Server host	No	0.0.0.0
LOG_LEVEL	Logging level	No	INFO

API Endpoints

The Massive API base URL is:

https://api.trademassive.com/v1

🧪 Testing

Test Locally

# Activate virtual environment
source venv/bin/activate

# Run server
python server.py

# In another terminal, test with curl or Python
python -c "
import asyncio
from server import get_stock_quote

async def test():
    result = await get_stock_quote('AAPL')
    print(result)

asyncio.run(test())
"

Test on Render

Once deployed, your server will be accessible at:

https://massive-mcp-server.onrender.com

📊 Usage Examples in ChatGPT

Once connected, you can ask ChatGPT natural language questions:

Stock Quotes:

• "What's the current price of Apple stock?"
• "Get me a quote for SPY"
• "Show me Tesla's current trading data"

Options Analysis:

• "Show me the options chain for AAPL expiring next month"
• "What are the call options available for SPY at 500 strike?"
• "Analyze the put options for TSLA"

Historical Data:

• "Get me the last 30 days of daily bars for NVDA"
• "Show me AAPL's 5-minute bars from today"
• "What was the trading volume for SPY last week?"

Market Snapshots:

• "Give me a complete market snapshot for Amazon"
• "Show me all trading data for Microsoft"

Ticker Search:

• "Find the ticker symbol for Nvidia"
• "Search for tech companies"

🔍 Troubleshooting

Common Issues

1. "MASSIVE_API_KEY not configured" error

• Ensure you've set the MASSIVE_API_KEY environment variable
• Check that your API key is valid and active

2. Server won't start locally

• Verify Python version (3.10+)
• Check all dependencies are installed: pip install -r requirements.txt
• Ensure port 8000 is not already in use

3. Render deployment fails

• Check build logs in Render dashboard
• Verify requirements.txt is in root directory
• Ensure environment variable is set correctly

4. ChatGPT can't connect to server

• Verify server is running (check Render logs)
• Confirm server URL is correct
• Check that server is publicly accessible

Logs

View logs in real-time on Render:

1. Go to your service in Render Dashboard
2. Click on "Logs" tab
3. Monitor for any errors or issues

🏗️ Project Structure

massive-mcp-server/
├── server.py              # Main MCP server with all tools
├── requirements.txt       # Python dependencies
├── render.yaml           # Render deployment configuration
├── .env.example          # Example environment variables
├── .gitignore           # Git ignore rules
└── README.md            # This file

🔐 Security

• Never commit your .env file or API keys to Git
• Keep your API key secure and rotate it regularly
• Use environment variables for all sensitive data
• The .gitignore file is configured to exclude .env

📝 License

This project is provided as-is for use with the OPTION TRADER ChatGPT project.

🤝 Support

For issues with:

• Massive API: Contact Massive Support
• Render Deployment: Check Render Documentation
• MCP Protocol: See MCP Documentation
• ChatGPT Integration: Visit OpenAI Help

🎉 Quick Start Checklist

• Python 3.10+ installed
• Massive API key obtained
• Dependencies installed (pip install -r requirements.txt)
• .env file created with API key
• Server tested locally (python server.py)
• Code pushed to GitHub
• Render account created
• Service deployed on Render
• Environment variable set on Render
• Server URL obtained from Render
• ChatGPT Developer Mode enabled
• MCP server connected to ChatGPT
• Tools tested in ChatGPT

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Built with ❤️ for the OPTION TRADER ChatGPT Project

Massive API MCP Server - Bringing real-time market data to your AI trading assistant