financeanalytics-data

Alpha Vantage Financial Data

xbluecode

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

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

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.

Use Cases

Extended AI Capabilities

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

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

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

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ 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.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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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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