MCP Stock Researcher Agent for Financial Analysis

import warnings
warnings.filterwarnings("ignore")

import os
import sys
import asyncio

# Enforce UTF-8 encoding for Windows terminal consoles
if sys.platform == "win32":
    sys.stdout.reconfigure(encoding="utf-8")

from dotenv import load_dotenv
from langchain_core.messages import HumanMessage
from langchain.agents import create_agent
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_mcp_adapters.client import MultiServerMCPClient

load_dotenv()

llm = ChatGoogleGenerativeAI(model="gemini-2.5-flash")

system_prompt = """
You are a financial research assistant helping users analyze stocks and financial data using Yahoo Finance.

Available Tools:
- get_historical_stock_prices: Get historical stock prices (ticker required)
- get_stock_info: Get comprehensive stock info (price, metrics, valuation)
- get_yahoo_finance_news: Get recent news articles for a stock
- get_stock_actions: Get dividends and stock splits history
- get_financial_statement: Get income statements or balance sheets
- get_holder_info: Get major/institutional holder data
- get_option_expiration_dates: Get options expiration dates
- get_option_chain: Get option chain pricing data
- get_recommendations: Get analyst buy/sell/hold consensus

Instructions:
1. ALWAYS use the relevant tool to fetch stock metrics before attempting to answer a stock-specific query.
2. Formulate concise, structured summaries citing exact dollar values and percentages.
"""

async def get_tools():
    # Launches the yahoo-finance-mcp-server via uvx stdio transport
    client = MultiServerMCPClient(
        {
            "yahoo-finance": {
                "command": "uvx",
                "args": ["yahoo-finance-mcp-server"],
                "transport": "stdio",
            }
        }
    )
    tools = await client.get_tools()
    return tools

async def finance_research(query):
    tools = await get_tools()
    agent = create_agent(model=llm, tools=tools, system_prompt=system_prompt)
    result = await agent.ainvoke({"messages": [HumanMessage(query)]})
    response = result["messages"][-1].text
    return response

query = "What is the current stock price and recent performance of Apple (AAPL)? Also show me the latest news."
response = asyncio.run(finance_research(query))
print(response)

Loaded 9 tools
Tools available: ['get_historical_stock_prices', 'get_stock_info', 'get_yahoo_finance_news', 'get_stock_actions', 'get_financial_statement', 'get_holder_info', 'get_option_expiration_dates', 'get_option_chain', 'get_recommendations']

Apple (AAPL) Current Price: $278.78 (up +$1.60/+0.58% today).
Performance (last month): Started at $275.25 on Nov 11, traded between $266.25 and $286.19, closing at $278.78 (+1.28%).

import subprocess
import sys
from langchain_core.tools import tool

@tool
def finance_researcher(query: str) -> str:
    """Research stocks using the Yahoo Finance MCP async function.
    Call this tool whenever you need to answer finance or stock-related questions.
    """
    code = f"""
import asyncio
from scripts.yahoo_mcp import finance_research
asyncio.run(finance_research("{query}"))
"""
    result = subprocess.run([sys.executable, '-c', code], capture_output=True, text=True)
    return result.stdout

system_prompt = """You are a professional stock research analyst specializing in financial analysis.

**Your Responsibilities:**
1. Analyze stock performance and financial metrics
2. Research company fundamentals
3. Provide data-driven investment recommendations
4. You must use available tools to answer user queries

**Analysis Framework:**
- Company name and ticker symbol
- Current stock price
- Key metrics: P/E ratio, Market Cap, Revenue
- Financial health assessment
- Clear recommendation: Buy, Hold, or Sell

**Important Guidelines:**
- Only respond to finance and stock market related questions
- For non-finance questions, politely decline: "I apologize, but I can only assist with stock market and financial analysis questions. Please ask me about stocks, companies, or financial metrics."
- Always cite specific data and metrics
- Maintain professional and objective tone

Provide concise, actionable insights for investors."""

from langchain.agents.middleware import TodoListMiddleware

model = ChatGoogleGenerativeAI(model='gemini-2.5-flash')

agent = create_agent(
    model=model,
    tools=[finance_researcher],
    system_prompt=system_prompt,
    middleware=[TodoListMiddleware()]
)

query = "Analyze Apple (AAPL) stock and its competitors like MSFT and Google. Present data clearly in a table."
response = agent.invoke({'messages': [HumanMessage(query)]})

write_todos arguments:
{
  "todos": [
    {"status": "in_progress", "content": "Research Apple (AAPL) stock performance."},
    {"status": "pending", "content": "Research Microsoft (MSFT) stock performance."},
    {"status": "pending", "content": "Research Google (GOOGL) stock performance."},
    {"status": "pending", "content": "Compile comparison metrics into a markdown table."}
  ]
}