Financial Analyst with MistralAI Agents API and MCP

A financial analysis application that uses MistralAI agents API with MCP servers for stock analysis and report generation.

Use Case

• Get real-time stock prices, historical data and analyst recommendations
• Generate comprehensive financial reports
• Save reports to files

Architecture

├── mcp_servers/
│   ├── stdio_yfinance_server.py
│   ├── stdio_report_gen_server.py
│   └── stdio_save_report_server.py
├── async_run_report_gen_mcp.py

├── mcp_servers/
│   ├── stdio_yfinance_server.py
│   ├── stdio_report_gen_server.py
│   └── stdio_save_report_server.py
├── async_run_report_gen_mcp.py

Main Application

• app.py: Chainlit interface with MistralAI agent integration

MCP Servers

• stdio_yfinance_server.py: Yahoo Finance data retrieval (prices, financials)
• stdio_report_gen_server.py: LLM-powered report generation using MistralAI
• stdio_save_report_server.py: Report persistence to files

Installation

pip install chainlit yfinance mcp mistralai loguru griffe

pip install chainlit yfinance mcp mistralai loguru griffe

Environment Setup

Set your MistralAI API key:

export MISTRAL_API_KEY="your_api_key_here"

export MISTRAL_API_KEY="your_api_key_here"

Set your Mistral API key in the servers: mcp_servers/stdio_report_gen_server.py

Usage

Run the application:

chainlit run app.py

chainlit run app.py

Open your browser and ask questions like:

• "What's the current stock price of AAPL?"
• "Get me a report on the historical stock prices of microsoft and save it to msft_historical.md"
• "Show me Microsoft's analyst recommendations"

The app will automatically use the appropriate MCP servers to fetch data and generate reports.