🔍 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

Related MCP server: competitor_analyzer-mcp-server

🏗️ 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

Built with ❤️ using FastMCP, OpenAI, and Gradio