Stock Market MCP Server

The Stock Market MCP Server bridges the gap between AI assistants and real‑time financial data. By exposing a rich set of tools that query the Finnhub API, it lets developers give Claude or other MCP‑compliant assistants instant access to market information without having to build their own data pipelines. This is especially valuable for building conversational finance apps, automated portfolio managers, or research assistants that need up‑to‑date quotes and news to answer user queries.

At its core, the server offers a collection of callable tools that cover the full spectrum of stock‑market information: from simple symbol lookups and current price retrieval to deeper financial metrics, market news feeds, and historical candle data. Each tool is a thin wrapper around Finnhub endpoints, making it trivial to add new capabilities or swap APIs later. The server also ships with a set of pre‑built prompts—such as stock_analysis and market_overview—that demonstrate how to combine multiple tool calls into coherent, context‑aware responses. These prompts serve as ready‑made templates for common analysis tasks and can be reused or extended by developers.

For developers using AI assistants, the server’s value lies in its ease of integration. Once running, an MCP client can invoke any tool by name, passing the required arguments as JSON. The server responds with structured data that can be parsed or fed directly into a language model for further synthesis. This eliminates the need to write custom adapters for each data source, allowing developers to focus on business logic rather than plumbing.

Typical use cases include:

• Conversational finance assistants that answer questions like “What’s the current price of AAPL?” or “Show me recent news about Tesla.”
• Portfolio monitoring tools that pull real‑time prices and financial ratios to compute risk metrics on the fly.
• Research bots that fetch historical candles, run technical analysis, and generate narrative summaries for investors.
• Educational platforms that let students experiment with real market data through natural language queries.

The server’s integration flow is straightforward: start the MCP server, add it as a local tool in Claude Desktop or any MCP‑compatible client, and begin calling its APIs. Because the server runs over stdio by default, it can be deployed in a variety of environments—from local machines to cloud functions—without any network configuration. Its lightweight Python implementation and reliance on the free tier of Finnhub make it an accessible entry point for hobbyists and professionals alike.