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Spring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
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Provides tools for automated company research, competitor identification, and business model analysis to generate comprehensive business intelligence. It enable
Provides tools for automated company research, competitor identification, and business model analysis to generate comprehensive business intelligence. It enables users to extract market keywords and synthesize competitive insights via AI-powered research capabilities.
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.
┌─────────────────┐
│ Gradio UI │
│ (Frontend) │
└────────┬────────┘
│
▼
┌─────────────────┐ ┌──────────────────┐
│ OpenAI GPT-4 │◄────►│ MCP Server │
│ (AI Analysis) │ │ (Research Tools)│
└─────────────────┘ └──────────────────┘
│
┌─────────┴─────────┐
│ Research Tools: │
│ • Company Info │
│ • Competitors │
│ • Business Model │
│ • Keywords │
└───────────────────┘
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 analysisgradio_app.py)Interactive web interface that:
Clone or download this repository
Run the setup script:
chmod +x setup.sh
./setup.sh
Configure your API key:
cp .env.example .env
# Edit .env and add your OpenAI API key
If you prefer manual setup:
# Create virtual environment
python3 -m venv venv
source venv/bin/activate
# Install dependencies
pip install -r requirements.txt
# 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
.env file or expose your OpenAI API key.env.example file is provided as a templateEdit mcp_research_server.py and add entries to the data dictionaries:
competitors_db (line ~70)business_data (line ~100)industry_keywords (line ~140)For production use, replace the sample data with real API calls:
In gradio_app.py, modify the model parameter:
model="gpt-4o-mini" # Change to "gpt-4o", "gpt-4-turbo", etc.
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
pip install -r requirements.txt
sk-Change the port in gradio_app.py:
demo.launch(server_port=7861) # Use different port
This project is provided as-is for educational and research purposes.
Contributions welcome! Feel free to:
Built with ❤️ using FastMCP, OpenAI, and Gradio
Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"mcp-research-server": {
"command": "npx",
"args": []
}
}
}