Stocks MCP Server

Stocks MCP – A Cloudflare‑Hosted Stock Data Interface for AI Assistants

The Stocks MCP server addresses a common pain point for developers building finance‑aware AI assistants: reliably querying real‑time market data from a lightweight, globally distributed endpoint. By hosting the MCP on Cloudflare Workers, the service delivers sub‑second latency and automatic scaling without requiring dedicated infrastructure or complex deployment pipelines. This makes it an ideal bridge between conversational agents and the fast‑moving world of stock prices, fundamentals, and market sentiment.

At its core, the server exposes a single MCP endpoint that accepts standard resources and tools calls. Clients can request the latest quote for any ticker, retrieve historical price series, or fetch company fundamentals. The MCP translates these requests into lightweight HTTP calls to public finance APIs and returns the data in a consistent JSON format. Developers can then embed these tools directly into their AI workflows, enabling agents to answer questions like “What was Apple’s closing price on March 3rd?” or “Show me the 30‑day moving average for TSLA” without leaving the conversation.

Key capabilities include:

• Real‑time market data: instant access to current bid/ask, volume, and last trade information for thousands of tickers.
• Historical series retrieval: flexible time‑range queries that return OHLCV data, suitable for charting or trend analysis.
• Fundamental metrics: earnings, revenue, and balance‑sheet figures that can enrich financial reasoning in an assistant.
• Stateless design: each request is independent, simplifying caching strategies and reducing server load.

Typical use cases span financial education tools, portfolio management assistants, and algorithmic trading prototypes. For example, a wealth‑management chatbot can pull live prices to calculate portfolio value on demand, while an investment research assistant can fetch earnings data to support recommendation generation. Because the MCP runs on Cloudflare Workers, it benefits from edge caching and global distribution, ensuring that users around the world experience low latency regardless of their location.

The integration workflow is straightforward: an AI client (such as the Cloudflare AI Playground) registers the MCP URL, then issues tool calls in natural language. The assistant interprets these calls, forwards them to the MCP, and incorporates the returned data into its response. This seamless loop lets developers focus on higher‑level reasoning while offloading the heavy lifting of data retrieval to a robust, serverless backend.