Stock Price MCP Server

Stock Price MCP Server

The Stock Price MCP Server bridges the gap between AI assistants and real‑time market data. By exposing a set of well‑defined tools, it allows Claude or other MCP‑compliant clients to query live stock prices, pull historical charts, and perform side‑by‑side comparisons—all without the assistant needing direct access to external APIs or databases. This is especially useful for developers building finance‑oriented chatbots, portfolio trackers, or investment research assistants that require up‑to‑date market information within a conversational context.

At its core, the server leverages the popular yfinance library to fetch data from Yahoo Finance. The tools are intentionally lightweight: one function returns the current price for any valid ticker, another streams historical data in CSV format (defaulting to a one‑month window but easily overridden), and a third compares two symbols in plain text. In addition to the toolset, the server offers a resource interface () that returns formatted price information. This dual approach—tools for granular queries and resources for quick look‑ups—provides flexibility in how AI assistants can request information, whether through explicit function calls or resource resolution.

Key capabilities include graceful handling of market closures and invalid symbols, ensuring that the assistant receives meaningful feedback rather than cryptic errors. The server also normalizes network failures by returning clear error messages, allowing developers to implement retry logic or fallback strategies within their AI workflows. Because the MCP protocol handles tool invocation and resource access uniformly, integrating this server into existing pipelines requires minimal changes: simply add the endpoint to the client’s MCP configuration and reference the desired tool names.

Real‑world scenarios where this server shines include automated financial news bots that pull current prices before generating summaries, investment advisors that compare competitor stocks on demand, or educational chatbots that fetch historical trends for teaching purposes. Developers can embed the server into a broader ecosystem—combining it with natural language understanding modules, decision‑making engines, or data visualization tools—to create end‑to‑end solutions that keep users informed and engaged.

In summary, the Stock Price MCP Server offers a concise, reliable interface for market data within AI assistants. Its combination of live price retrieval, historical access, comparison logic, and resource exposure makes it a versatile component for any finance‑focused application that relies on the Model Context Protocol to extend its capabilities.