from mcp.server.fastmcp import FastMCP
from finance_crew import run_financial_analysis
# create FastMCP instance
mcp = FastMCP("financial-analyst")
@mcp.tool()
def analyze_stock(query: str) -> str:
"""
Analyzes stock market data based on the query and generates executable Python code for analysis and visualization.
Returns a formatted Python script ready for execution.
The query is a string that must contain the stock symbol (e.g., TSLA, AAPL, NVDA, etc.),
timeframe (e.g., 1d, 1mo, 1y), and action to perform (e.g., plot, analyze, compare).
Example queries:
- "Show me Tesla's stock performance over the last 3 months"
- "Compare Apple and Microsoft stocks for the past year"
- "Analyze the trading volume of Amazon stock for the last month"
Args:
query (str): The query to analyze the stock market data.
Returns:
str: A nicely formatted python code as a string.
"""
try:
result = run_financial_analysis(query)
return result
except Exception as e:
return f"Error: {e}"
@mcp.tool()
def save_code(code: str) -> str:
"""
Expects a nicely formatted, working and executable python code as input in form of a string.
Save the given code to a file stock_analysis.py, make sure the code is a valid python file, nicely formatted and ready to execute.
Args:
code (str): The nicely formatted, working and executable python code as string.
Returns:
str: A message indicating the code was saved successfully.
"""
try:
with open('stock_analysis.py', 'w') as f:
f.write(code)
return "Code saved to stock_analysis.py"
except Exception as e:
return f"Error: {e}"
@mcp.tool()
def run_code_and_show_plot() -> str:
"""
Run the code in stock_analysis.py and generate the plot
"""
with open('stock_analysis.py', 'r') as f:
exec(f.read())
# Run the server locally
if __name__ == "__main__":
mcp.run(transport='stdio')
