Custom Python MCP Server

Quick Start

Create MCP Server

Create a new file app.py with your custom MCP server implementation:

import yfinance as yf
from mcp.server.fastmcp import FastMCP

mcp = FastMCP("stock_prices")

@mcp.tool()
async def get_stock_price(ticker: str) -> str:
    """Get the current stock price for a given ticker symbol.
    
    Args:
        ticker: Stock ticker symbol (e.g., AAPL, MSFT, GOOG)
        
    Returns:
        Current stock price as a string
    """
    if not ticker:
        return "No ticker provided"
    try:
        stock = yf.Ticker(ticker)
        info = stock.info
        current_price = info.get('currentPrice') or info.get('regularMarketPrice')
        if not current_price:
            return f"Could not retrieve price for {ticker}"
        return f"${current_price:.2f}"
        
    except Exception as e:
        return f"Error: {str(e)}"

if __name__ == "__main__":
    mcp.run(transport='stdio')

Install Dependencies

Install the required dependencies in a conda environment:

pip install yfinance mcp

Create Agent Integration

Create a new file stock_agent.py with the following code:

from praisonaiagents import Agent, MCP

agent = Agent(
    instructions="""You are a helpful assistant that can check stock prices and perform other tasks.
    Use the available tools when relevant to answer user questions.""",
    llm="gpt-4o-mini",
    tools = MCP("/path/to/python /path/to/app.py")
)

# NOTE: Replace with your actual Python path and app.py file path

agent.start("What is the stock price of Tesla?")

Run the Agent

Execute your script:

python stock_agent.py

Requirements

Python 3.10 or higher
Conda for environment management
yfinance package for stock data
mcp-python-sdk for MCP server implementation
OpenAI API key (for the agent’s LLM)

Features

Custom Tools

Create your own custom tools with Python.

MCP Integration

Seamless integration with Model Context Protocol.

Type Hints

Strong typing for better code reliability.

Async Support

Built-in support for asynchronous functions.

Implementation Details

FastMCP Class

The FastMCP class from the mcp-python-sdk package provides a simple way to create MCP servers in Python:

from mcp.server.fastmcp import FastMCP

# Create an MCP server with a name
mcp = FastMCP("my_tools")

# Define a tool using the @mcp.tool decorator
@mcp.tool()
async def my_tool(param1: str, param2: int) -> str:
    """Tool description with clear documentation.
    
    Args:
        param1: Description of param1
        param2: Description of param2
        
    Returns:
        Description of the return value
    """
    # Tool implementation
    return f"Processed {param1} with {param2}"

# Run the server with stdio transport
if __name__ == "__main__":
    mcp.run(transport='stdio')

Agent Integration

To use your custom MCP server with PraisonAI agents, use the MCP class to specify the command to run your Python script:

from praisonaiagents import Agent, MCP

agent = Agent(
    instructions="Agent instructions",
    llm="gpt-4o-mini",
    tools=MCP(
        command="python",  # Or full path to Python
        args=["path/to/your/mcp_server.py"]  # Path to your MCP server script
    )
)

MCP

​Custom Python MCP Server

​Quick Start

​Features