Portfolio Manager MCP Server

A Model Context Protocol (MCP) server that provides tools and resources for managing and analyzing investment portfolios.

Features

• Portfolio Management: Create and update investment portfolios with stocks and bonds
• Market Data: Fetch real-time stock price information and relevant news
• Analysis: Generate comprehensive portfolio reports and performance analysis
• Recommendations: Get personalized investment recommendations based on portfolio composition
• Visualization: Create visual representations of portfolio allocation

Installation

1. Clone this repository:

   git clone https://github.com/ikhyunAn/portfolio-manager-mcp.git
   cd portfolio-manager-mcp
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Set up API keys (optional):

   export ALPHA_VANTAGE_API_KEY="your_key_here"
   export NEWS_API_KEY="your_key_here"
   

   Alternatively, create a .env file in the root of the directory and store the API keys

Usage

Running the Server

You can run the server in two different modes:

1. Stdio Transport (default, for Claude Desktop integration):

   python main.py   # alternate commands: i.e.) python3, python3.11
   

2. SSE Transport (for HTTP-based clients):

   python main.py --sse
   

Integration with Claude Desktop

Add the server to your Claude Desktop configuration file:

{
  "mcpServers": {
    "portfolio-manager": {
      "command": "python",      // may use different command
      "args": ["/path/to/portfolio-manager-mcp/main.py"],
      "env": {
        "ALPHA_VANTAGE_API_KEY": "your_key_here",
        "NEWS_API_KEY": "your_key_here"
      }
    }
  }
}

If you choose to run your server in a virtual environment, then your configuration file will look like:

{
  "mcpServers": {
    "portfolio-manager": {
      "command": "/path/to/portfolio-manager-mcp/venv/bin/python",
      "args": ["/path/to/portfolio-manager-mcp/main.py"],
      "env": {
        "PYTHONPATH": "/path/to/portfolio-manager-mcp",
        "ALPHA_VANTAGE_API_KEY": "your_key_here",
        "NEWS_API_KEY": "your_key_here"
      }
    }
  }
}

To run it in a virtual environment:

# Create a virtual environment
python3 -m venv venv

# Activate the virtual environment
source venv/bin/activate  # On macOS/Linux
# or
# venv\Scripts\activate   # On Windows

# Install dependencies
pip install -r requirements.txt

# Run the server
python3 main.py

Or use the MCP CLI for easier installation:

mcp install main.py

Example Queries