Used to search for and retrieve basic company information and background data through the Wikipedia API to support automated business research.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Research ServerAnalyze NVIDIA's business model and identify their top competitors."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
š 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.
š 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
šļø Architecture
āāāāāāāāāāāāāāāāāāā
ā Gradio UI ā
ā (Frontend) ā
āāāāāāāāāā¬āāāāāāāāā
ā
ā¼
āāāāāāāāāāāāāāāāāāā āāāāāāāāāāāāāāāāāāāā
ā OpenAI GPT-4 āāāāāāāŗā MCP Server ā
ā (AI Analysis) ā ā (Research Tools)ā
āāāāāāāāāāāāāāāāāāā āāāāāāāāāāāāāāāāāāāā
ā
āāāāāāāāāāā“āāāāāāāāāā
ā Research Tools: ā
ā ⢠Company Info ā
ā ⢠Competitors ā
ā ⢠Business Model ā
ā ⢠Keywords ā
āāāāāāāāāāāāāāāāāāāāāš Components
1. MCP Research Server (mcp_research_server.py)
FastMCP server providing research tools:
search_company_info()- Search for basic company informationfind_competitors()- Find competitor companiesanalyze_company_business()- Analyze business model and activitiesextract_market_keywords()- Extract market and industry keywordsgenerate_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
š Quick Start
Prerequisites
Python 3.8 or higher
OpenAI API key (Get one here)
Installation
Clone or download this repository
Run the setup script:
chmod +x setup.sh ./setup.shConfigure 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.txtš» Usage
Start the Application
# Activate virtual environment (if not already active)
source venv/bin/activate
# Run the Gradio app
python gradio_app.pyThe application will start on http://localhost:7860
Using the Interface
Enter a company name (e.g., "Apple", "Tesla", "Netflix")
Enter your OpenAI API key (required for AI analysis)
Click "Research Company" to start the analysis
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
š¦ 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
š§ How It Works
User Input: User enters company name in Gradio interface
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
AI Synthesis: OpenAI GPT-4 processes all research data and generates:
Executive summary
Key insights
Market positioning analysis
Results Display: Formatted report shown in Gradio UI
šÆ 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
š Security Notes
Never commit your
.envfile or expose your OpenAI API keyUse environment variables for sensitive information
The
.env.examplefile is provided as a template
š ļø 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.š Project Structure
mcp2_test/
āāā README.md # This file
āāā requirements.txt # Python dependencies
āāā .env.example # Environment variables template
āāā setup.sh # Setup script
āāā mcp_research_server.py # MCP server with research tools
āāā gradio_app.py # Gradio web applicationš 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 portš 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
š License
This project is provided as-is for educational and research purposes.
š¤ Contributing
Contributions welcome! Feel free to:
Add more MCP tools
Improve the UI/UX
Integrate additional APIs
Enhance the AI prompts
Add export functionality
š” Learn More
Built with ā¤ļø using FastMCP, OpenAI, and Gradio
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