financeanalytics-data

Alpha Vantage Financial Data

by xbluecode

Get real-time stock price for NVDA, NVIDIA, and AMA plus historical data for market research via Alpha Vantage Financial

Integrates with Alpha Vantage API to provide stock quotes and historical data for financial analysis and market research tasks.

github stars

9

Requires Alpha Vantage API keySupports multiple time intervals

best for

  • / Financial analysts tracking market data
  • / Investment research and portfolio analysis
  • / Building trading algorithms with historical data

capabilities

  • / Get current stock quotes by symbol
  • / Fetch historical stock data (daily/weekly/monthly)
  • / Query market prices for financial analysis
  • / Access Alpha Vantage financial datasets

what it does

Retrieves real-time stock quotes and historical price data from Alpha Vantage API for financial analysis.

about

Alpha Vantage Financial Data is a community-built MCP server published by xbluecode that provides AI assistants with tools and capabilities via the Model Context Protocol. Get real-time stock price for NVDA, NVIDIA, and AMA plus historical data for market research via Alpha Vantage Financial It is categorized under finance, analytics data.

how to install

You can install Alpha Vantage Financial Data 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.

license

MIT

Alpha Vantage Financial Data is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Financial Data - MCP Server

smithery badge

This is an MCP server that provides access to the Alpha Vantage API, allowing stock data retrieval to be used as context to LLMs.

<a href="https://glama.ai/mcp/servers/czslwc47w9"><img width="380" height="200" src="https://glama.ai/mcp/servers/czslwc47w9/badge" alt="findata-mcp-server MCP server" /></a>

Available Features

  • getStockQuote: Get the current quote for a stock.
  • getHistoricalData: Get historical data for a stock (daily, weekly, or monthly).
  • (More tools will be added later for technical analysis, company overview, etc.)

Setup

Installing via Smithery

To install Financial Data Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install findata-mcp-server --client claude

Manual Installation

npm install findata-mcp-server

Usage in Host

  1. Obtain an API key from Alpha Vantage https://www.alphavantage.co/support/#api-key.

  2. Configure your MCP client (e.g., Claude Desktop) to connect to the server:

{
  "mcpServers": {
    "alphaVantage": {
      "command": "npx",
      "args": ["-y", "findata-mcp-server"],
      "env": {
        "ALPHA_VANTAGE_API_KEY": "PUT_YOUR_API_KEY_HERE"
      }
    }
  }
}

Tools

getStockQuote

Get the current quote for a stock.

Input:

symbol: The stock symbol (e.g., AAPL) Output Example:

getHistoricalData

Get historical data for a stock.

Input:

  • symbol: the stock symbol (e.g., AAPL)
  • interval: the time interval for the data (daily, weekly, or monthly) (optional, default: daily)
  • outputsize: the size of the output (compact or full) (optional, default: compact) Output:

JSON object containing the historical data. The structure of the output depends on the interval parameter.

Contributing

Contributions are welcome! Please open an issue or pull request.

License

MIT

FAQ

What is the Alpha Vantage Financial Data MCP server?
Alpha Vantage Financial Data is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Alpha Vantage Financial Data?
This profile displays 31 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.731 reviews
  • Hiroshi Mensah· Dec 20, 2024

    Alpha Vantage Financial Data is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Mia Ghosh· Dec 8, 2024

    Alpha Vantage Financial Data has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Lucas Gonzalez· Nov 27, 2024

    According to our notes, Alpha Vantage Financial Data benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Hiroshi Srinivasan· Nov 11, 2024

    Alpha Vantage Financial Data is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Mia Anderson· Oct 18, 2024

    Alpha Vantage Financial Data is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Kaira Khanna· Oct 2, 2024

    According to our notes, Alpha Vantage Financial Data benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Aarav Robinson· Sep 25, 2024

    We evaluated Alpha Vantage Financial Data against two servers with overlapping tools; this profile had the clearer scope statement.

  • Piyush G· Sep 9, 2024

    According to our notes, Alpha Vantage Financial Data benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Anaya Ghosh· Sep 9, 2024

    I recommend Alpha Vantage Financial Data for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Hana Flores· Sep 1, 2024

    Alpha Vantage Financial Data reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

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