About InvestMCP
InvestMCP is a suite of MCP servers that gives Claude access to stock fundamentals, technical indicators, and financial news sentiment. It supports conversational stock analysis using financial data sources.
Key features
- 01Fundamental stock data
- 02Technical indicators and chart patterns
- 03Financial news and sentiment analysis
Use cases
- 01Reviewing company financial metrics
- 02Examining technical signals for a stock
- 03Assessing sentiment in company news
MCP support
Its MCP servers expose stock data, technical analysis, and financial news sentiment to Claude. Stock screening, investment advice, and portfolio tracking are listed as planned, not implemented features.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEInvestMCP
InvestMCP is a comprehensive suite of Model Context Protocol (MCP) servers that transform Claude AI into a powerful stock analysis assistant. This project enables seamless integration between Claude and financial data sources, allowing for natural language investment analysis through conversation.
🚀 Features
Implemented Servers
-
Stock Data Server: Access fundamental financial data including P/E ratios, dividend yields, revenue growth, and more.
-
Technical Analysis Server: Generate technical indicators like RSI, MACD, moving averages, and identify chart patterns.
-
Financial News Server: Analyze news sentiment and track breaking stories about companies to incorporate market sentiment into investment decisions.
Planned Servers
-
Stock Screener Server: Filter stocks based on custom criteria to discover investment opportunities.
-
Investment Advisor Server: Receive personalized investment recommendations based on risk tolerance and goals.
-
Portfolio Tracker Server: Track portfolio performance and get rebalancing suggestions.
📋 Requirements
- Python 3.10+
- Claude Desktop app with MCP support
- Required Python packages:
- mcp[cli]>=1.4.0
- yfinance>=0.2.30
- pandas>=2.0.0
- numpy>=1.24.0
- requests>=2.31.0
- nltk>=3.8.1
🔧 Installation
- Clone this repository:
git clone https://github.com/arrpitk/InvestMCP.git
cd InvestMCP
Configure Claude Desktop:
- Open Claude Desktop settings
- Navigate to Developer tab
- Click "Edit Config"
- Add the MCP server configuration (see example below)
🔍 Usage
Claude Desktop Configuration
json
{
"mcpServers": {
"stock-data": {
"command": "python3",
"args": ["/path/to/InvestMCP/servers/stock_data_server.py"]
},
"technical-analysis": {
"command": "python3",
"args": ["/path/to/InvestMCP/servers/technical_analysis_server.py"]
},
"financial-news": {
"command": "python3",
"args": ["/path/to/InvestMCP/servers/financial_news_server.py"],
"env": {
"NEWS_API_KEY": "your-news-api-key-here"
}
}
}
}
Example Conversations
Once configured, you can talk to Claude naturally about stocks:
- "What are the key financial metrics for AAPL?"
- "Show me the technical analysis for MSFT including RSI and MACD."
- "What's the current news sentiment around Tesla?"
- "Compare the fundamentals of AMZN and GOOGL."
🔜 Roadmap
- Add Stock Screener functionality
- Implement Investment Advisor capabilities
- Add Portfolio Tracking and management
- Create interactive visualizations for technical analysis
- Add historical backtesting of investment strategies
📝 License
This project is licensed under the MIT License - see the LICENSE file for details.
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
📢 Acknowledgements
- Model Context Protocol by Anthropic
- yfinance for financial data
- NLTK for sentiment analysis
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.