Adity-star/mcp-yfinance-server

This project sets up a **stock Price server** powered by the **Yahoo Finance (YFinance)** API and built for seamless integration with **MCP (Model Control Protocol)**.
It allows AI agents or clients to:
- Retrieve real-time stock data
- Manage a watchlist
- Perform full stock analysis
- Run full technical indicators
- And much more
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🪙 Start Simple: Build a Crypto Price Tracker First
Before diving into the full-blown stock server, I recommend starting with this simple crypto tracker built with Python + MCP 👇
🔗 GitHub Repo:
https://github.com/Adity-star/mcp-crypto-server
> You'll learn how to:
> - Use MCP to expose crypto tools like get_price("BTC")
> - Build an API with FastAPI
> - Fetch real-time prices using the Alpaca API
🔗 Related Projects
Explore more of my work:
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- LangChain-Mastery: Everything you need to master LangChain for building powerful LLM applications.
- Complete Data Science: A deep dive into Data Science AI concepts, tools, and projects and all the material for learning and interview preparation.
- Reinforcement-Learning: Hands-on experiments and theory in Reinforcement Learning.
- CompleteRAG: End-to-end implementation of Retrieval-Augmented Generation (RAG) systems.
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📈 Then Level Up: Build the yFinance Stock Server
Once you're familiar with the flow, move on to this more advanced stock tracker 💹
🔗 GitHub Repo:
https://github.com/Adity-star/mcp-yfinance-server
📝 Detailed Blog:
👉 How I Built My Own Stock Server with Python, yFinance, and a Touch of Nerdy Ambition
> Includes:
> - Watchlists
> - Real-time(ish) price updates
> - Technical summaries
> - A full-featured dashboard
> - Trend + momentum indicators
> - Watchlist management
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📦 Step 1: Set Up the Environment (with uv)
We use **uv** — a modern, ultra-fast Python package manager — to manage our project environment.
🛠️ Installation & Setup
Run the following commands in your terminal:
📥 Install the project
Once your pyproject.toml is set up with dependencies, run:
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🚀 Step 2: Running the MCP Server
Once your environment is ready, start the stock server:
🧪 Want a quick test first?
Try checking the tools first:
📄 Curious how the full server works?
Explore the source code here:
🔗 yf_server.py › GitHub
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🛠️ MCP Tool Reference
The server exposes many tools for AI agents and CLI users.
Here are some important tools, check out the complete tools list here:
📦 Tool List
| Tool Name | Description |
|-------------------------------|-----------------------------------------------------------------------------|
| add_to_watchlist | Add a stock ticker to your personal watchlist. |
| analyze_stock |Perform a 1-month technical trend analysis (RSI, MACD, MAs).. |
| get_technical_summary |Generate a comprehensive technical summary including indicators & signals.. |
| get_watchlist_prices | Fetch the most recent prices for all watchlisted tickers. |
| get_trend_analysiss | Analyze recent trend shifts, patterns, and divergences.. |
| get_stock_price | Retrieve the current price for a given ticker symbol. |
| get_volatility_analysis | Calculate historical volatility and ATR metrics.. |
| compare_stocks | Compare two stock prices (useful for relative performance analysis). |
> ✅ Total: 18 powerful tools to analyze and monitor stocks with precision.
🧠 Use Cases
These tools are ideal for:
- 📊 Dynamic watchlist management
- 🔁 Trend and momentum detection