🔍 Company Research Agent with MCP + OpenAI + Gradio

An intelligent company research and competitive analysis tool that combines the power of Model Context Protocol (MCP), OpenAI GPT-4, and Gradio to deliver comprehensive business intelligence.

🌟 Features

• Automated Company Research: Search for company information using MCP tools
• Competitor Analysis: Automatically identify and analyze competitors
• Business Model Analysis: Understand company operations and revenue streams
• Market Keywords Extraction: Extract relevant keywords describing the competitive landscape
• AI-Powered Insights: OpenAI synthesizes research into actionable executive summaries
• Interactive UI: Beautiful Gradio interface for easy interaction

🏗️ Architecture

┌─────────────────┐
│  Gradio UI      │
│  (Frontend)     │
└────────┬────────┘
         │
         ▼
┌─────────────────┐      ┌──────────────────┐
│  OpenAI GPT-4   │◄────►│  MCP Server      │
│  (AI Analysis)  │      │  (Research Tools)│
└─────────────────┘      └──────────────────┘
                                   │
                         ┌─────────┴─────────┐
                         │  Research Tools:  │
                         │  • Company Info   │
                         │  • Competitors    │
                         │  • Business Model │
                         │  • Keywords       │
                         └───────────────────┘

📋 Components

1. MCP Research Server (mcp_research_server.py)

FastMCP server providing research tools:

• search_company_info() - Search for basic company information
• find_competitors() - Find competitor companies
• analyze_company_business() - Analyze business model and activities
• extract_market_keywords() - Extract market and industry keywords
• generate_competitive_report() - Generate full competitive analysis

2. Gradio Application (gradio_app.py)

Interactive web interface that:

• Accepts company name and OpenAI API key as inputs
• Orchestrates MCP tool calls for data gathering
• Uses OpenAI to generate intelligent summaries
• Displays results in an organized, user-friendly format

🚀 Quick Start

Prerequisites

• Python 3.8 or higher
• OpenAI API key (Get one here)

Installation

1. Clone or download this repository

2. Run the setup script:

   chmod +x setup.sh
   ./setup.sh
   

3. Configure your API key:

   cp .env.example .env
   # Edit .env and add your OpenAI API key
   

Manual Installation

If you prefer manual setup:

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

💻 Usage

Start the Application

# Activate virtual environment (if not already active)
source venv/bin/activate

# Run the Gradio app
python gradio_app.py

The application will start on http://localhost:7860

Using the Interface

1. Enter a company name (e.g., "Apple", "Tesla", "Netflix")
2. Enter your OpenAI API key (required for AI analysis)
3. Click "Research Company" to start the analysis
4. View results:
   • Executive Summary (AI-generated)
   • Full Report (expand accordion)
   • Market Keywords (expand accordion)

Example Companies to Try

• Technology: Apple, Microsoft, Google, Amazon, Meta
• Automotive: Tesla, Ford, General Motors
• Entertainment: Netflix, Disney
• Consumer Goods: Nike, Coca-Cola, Starbucks

📦 Dependencies

• fastmcp - Model Context Protocol server framework
• gradio - Web UI framework
• openai - OpenAI API client
• requests - HTTP library for web requests
• beautifulsoup4 - HTML parsing (for future web scraping)
• python-dotenv - Environment variable management

🔧 How It Works

1. User Input: User enters company name in Gradio interface
2. MCP Tools: Application calls MCP research tools to gather data:
   • Company information from Wikipedia API
   • Competitor identification from database
   • Business model analysis
   • Market keyword extraction
3. AI Synthesis: OpenAI GPT-4 processes all research data and generates:
   • Executive summary
   • Key insights
   • Market positioning analysis
4. Results Display: Formatted report shown in Gradio UI

🎯 Use Cases

• Competitive Intelligence: Understand your competitors quickly
• Market Research: Identify market trends and keywords
• Investment Analysis: Research companies for investment decisions
• Business Strategy: Inform strategic planning with competitive data
• Sales Enablement: Prepare for sales conversations with prospect research

🔐 Security Notes

• Never commit your .env file or expose your OpenAI API key
• Use environment variables for sensitive information
• The .env.example file is provided as a template

🛠️ Customization

Adding More Companies

Edit mcp_research_server.py and add entries to the data dictionaries:

• competitors_db (line ~70)
• business_data (line ~100)
• industry_keywords (line ~140)

Using Real APIs

For production use, replace the sample data with real API calls:

• Business data APIs (Crunchbase, PitchBook)
• Financial APIs (Alpha Vantage, Yahoo Finance)
• News APIs (NewsAPI, Google News)
• Web scraping (requests + BeautifulSoup)

Changing OpenAI Model

In gradio_app.py, modify the model parameter:

model="gpt-4o-mini"  # Change to "gpt-4o", "gpt-4-turbo", etc.

📊 Project Structure

mcp2_test/
├── README.md                    # This file
├── requirements.txt             # Python dependencies
├── .env.example                 # Environment variables template
├── setup.sh                     # Setup script
├── mcp_research_server.py       # MCP server with research tools
└── gradio_app.py               # Gradio web application

🐛 Troubleshooting

"Module not found" errors

pip install -r requirements.txt

"Invalid API key" error

• Check your OpenAI API key in the input field
• Ensure you have credits in your OpenAI account
• Verify the key starts with sk-

Port already in use

Change the port in gradio_app.py:

demo.launch(server_port=7861)  # Use different port

🚀 Future Enhancements

• [ ] Real-time web scraping for live data
• [ ] Integration with business intelligence APIs
• [ ] Export reports to PDF/CSV
• [ ] Historical trend analysis
• [ ] Multi-company comparison view
• [ ] Financial metrics integration
• [ ] News sentiment analysis
• [ ] Custom report templates

📝 License

This project is provided as-is for educational and research purposes.

🤝 Contributing

Contributions welcome! Feel free to:

• Add more MCP tools
• Improve the UI/UX
• Integrate additional APIs
• Enhance the AI prompts
• Add export functionality

💡 Learn More

• FastMCP Documentation
• Gradio Documentation
• OpenAI API Reference
• Model Context Protocol

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Built with ❤️ using FastMCP, OpenAI, and Gradio