MCP server
by narumiruna
Access real-time financial data and market trends with Yahoo Finance tools for in-depth investment research and analysis
Fetches real-time and historical stock data, financial news, and market information directly from Yahoo Finance. Provides comprehensive investment research capabilities without requiring API keys.
Yahoo Finance is a community-built MCP server published by narumiruna that provides AI assistants with tools and capabilities via the Model Context Protocol. Access real-time financial data and market trends with Yahoo Finance tools for in-depth investment research and analysis It is categorized under finance. This server exposes 5 tools that AI clients can invoke during conversations and coding sessions.
You can install Yahoo Finance in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport. This server supports remote connections over HTTP, so no local installation is required.
MIT
Yahoo Finance is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Yahoo Finance is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Useful MCP listing: Yahoo Finance is the kind of server we cite when onboarding engineers to host + tool permissions.
Yahoo Finance reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend Yahoo Finance for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Yahoo Finance is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, Yahoo Finance benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We wired Yahoo Finance into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Strong directory entry: Yahoo Finance surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Yahoo Finance has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Yahoo Finance has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
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A simple MCP server for Yahoo Finance using yfinance. This server provides a set of tools to fetch stock data, news, and other financial information.
<a href="https://glama.ai/mcp/servers/@narumiruna/yfinance-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@narumiruna/yfinance-mcp/badge" /> </a>yfinance_get_ticker_info
symbol (string): The stock symbol.yfinance_get_ticker_news
symbol (string): The stock symbol.yfinance_search
query (string): The search query (ticker symbol or company name).search_type (string): Type of search results to retrieve (options: "all", "quotes", "news").yfinance_get_top
sector (string): The sector to get.top_type (string): Type of top companies to retrieve (options: "top_etfs", "top_mutual_funds", "top_companies", "top_growth_companies", "top_performing_companies").top_n (number, optional): Number of top entities to retrieve (default 10).yfinance_get_price_history
symbol (string): The stock symbol.period (string, optional): Time period to retrieve data for (e.g. '1d', '1mo', '1y'). Default is '1mo'.interval (string, optional): Data interval frequency (e.g. '1d', '1h', '1m'). Default is '1d'.chart_type (string, optional): Type of chart to generate. If not specified, returns price data as markdown table. Options:
chart_type is not specified: Returns historical price data as a markdown tablechart_type is specified: Returns a base64-encoded WebP image for efficient token usageYou can use this MCP server via uv (Python package installer), Docker, or local development.
{
"mcpServers": {
"yfmcp": {
"command": "uvx",
"args": ["yfmcp@latest"]
}
}
}
Add the following configuration to your MCP server configuration file:
{
"mcpServers": {
"yfmcp": {
"command": "docker",
"args": ["run", "-i", "--rm", "narumi/yfinance-mcp"]
}
}
}
For local development, add the following configuration to your MCP server configuration file:
{
"mcpServers": {
"yfmcp": {
"command": "uv",
"args": [
"run",
"--directory",
"/path/to/yfinance-mcp",
"yfmcp"
]
}
}
}
Replace /path/to/yfinance-mcp with the actual path to your local repository.
This repository includes a demo chatbot built with Chainlit that provides a conversational interface to the Yahoo Finance MCP server.
uv sync --extra dev
# Recommended: start from the template
cp .env.example .env
# For OpenAI
OPENAI_API_KEY=your_openai_api_key
DEFAULT_MODEL=gpt-4.1
# For LiteLLM (alternative)
LITELLM_API_KEY=your_litellm_api_key
LITELLM_BASE_URL=your_litellm_base_url
DEFAULT_MODEL=gpt-4.1
uv run chainlit run demo.py
The chatbot will be available at http://localhost:8000.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.