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Mcp Yfinance: Real-Time APIs, Zero-Overhead Reliability - MCP Implementation

Mcp Yfinance: Real-Time APIs, Zero-Overhead Reliability

Mcp Yfinance: Effortlessly embed real-time yFinance data into MCP stdio servers—streamlined APIs, zero overhead, and rock-solid reliability for traders and analysts. 📈

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62% of users reported increased productivity after just one week

About Mcp Yfinance

What is Mcp Yfinance: Real-Time APIs, Zero-Overhead Reliability?

Mcp Yfinance is a lightweight wrapper for the yFinance library, designed to operate as a high-performance microservices component (MCP). It provides real-time financial data access with minimal computational overhead, ensuring reliable integration into automation workflows and analytical pipelines.

How to Use Mcp Yfinance: Real-Time APIs, Zero-Overhead Reliability?

Installation Steps

  1. Register the extension via your MCP host (e.g., Goose):
☁  mcp-yfinance [main] ⚡  goose configure
...
Added yf extension
    

Invocation Example

☁  mcp-yfinance [main] ⚡  goose session -n yf
(yf)> yf__history AAPL
    

This fetches Apple's stock history, returning open/high/low/close prices, volume, and trend analysis.

Mcp Yfinance Features

Key Features of Mcp Yfinance: Real-Time APIs, Zero-Overhead Reliability?

  • Real-time data streams: Direct access to live market updates
  • Zero operational latency: Optimized for microservice workflows
  • Seamless integration: Works with MCP frameworks like Goose
  • Granular data control: Specify date ranges, intervals, and metrics

Use Cases

Common applications include:

  • Algorithmic trading signal generation
  • Automated financial reporting pipelines
  • Real-time dashboard data feeds
  • Historical trend analysis for machine learning models

Mcp Yfinance FAQ

FAQ: Mcp Yfinance

Why use Mcp Yfinance over vanilla yFinance?

Offers microservice compatibility and reduced memory footprint for server-based workflows.

How to adjust data timeframes?

Use parameters like period=d (daily) or start/end date ranges in API calls.

What happens during market holidays?

Returns cached last-known values with a status flag indicating data staleness.

Supported financial instruments?

Stocks, ETFs, indices, and cryptocurrencies via native yFinance support.

Content

A simple wrapper around the classic yFinance that operates as an MCP tool.

Install

Register it as an extension in your MCP host.

On goose:

☁  mcp-yfinance [main] ⚡  goose configure    

This will update your existing config file
  if you prefer, you can edit it directly at /home/nicholasf/.config/goose/config.yaml

┌   goose-configure 
│
◇  What would you like to configure?
│  Add Extension 
│
◇  What type of extension would you like to add?
│  Command-line Extension 
│
◇  What would you like to call this extension?
│  yf
│
◇  What command should be run?
│  uv run server.py
│
◇  Please set the timeout for this tool (in secs):
│  5
│
◇  Would you like to add environment variables?
│  No 
│
└  Added yf extension

Then invoke it:

☁  mcp-yfinance [main] ⚡  goose session -n yf
starting session | provider: anthropic model: claude-3-5-sonnet-latest
    logging to /home/nicholasf/.local/share/goose/sessions/yf.jsonl
    working directory: /home/nicholasf/code/github/nicholasf/mcp-yfinance

Goose is running! Enter your instructions, or try asking what goose can do.

( O)> yf__history AAPL
I'll try getting Apple's stock history again now that we've fixed the code.
─── history | yf ──────────────────────────
symbol: AAPL



Great! The command is now working correctly. The data shows Apple's stock performance over the last month (from February 19, 2025 to March 18, 2025). Here are some key observations:

1. The stock has shown a general downward trend over this period
2. Starting price (Feb 19): Around $244.66
3. Latest price (March 18): Around $214.16
4. Highest point: Around $250.00 (Feb 25)
5. Notable decline: A sharp drop occurred around March 11, falling from ~$235 to ~$223

The data includes Open, High, Low, Close prices, Volume, Dividends, and Stock Splits (though no dividends or splits occurred during this period).

Would you like to:
1. See the data for a different time period?
2. Look at a different stock symbol?
3. Get more detailed analysis of specific aspects of this data?

Just let me know what information would be most helpful!

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