Search Stock News MCP Server

The Search Stock News MCP Server is a lightweight, plug‑in‑ready service that bridges AI assistants with real‑time financial news. By exposing a set of typed, declarative endpoints over the Model Context Protocol (MCP), it lets developers ask an AI for up‑to‑date information about any publicly traded company without writing custom webhooks or parsing RSS feeds. This solves a common pain point for finance‑focused applications: the need to keep data fresh, reliable, and easily queryable from within an assistant’s conversational flow.

At its core, the server taps into the Tavily API to perform keyword‑driven searches across a curated set of news sources. Clients send a simple JSON payload—containing the ticker symbol, company name, and optional filters such as maximum results or minimum relevance score—and receive a structured list of headline snippets, URLs, and timestamps. The service also supports domain whitelisting (e.g., “reuters.com”, “bloomberg.com”) so that users can restrict results to trusted outlets, and a configurable search depth that balances speed against comprehensiveness.

For developers building AI‑powered trading tools, market analysis dashboards, or personal finance assistants, this server provides several key advantages:

• Zero‑code integration: Any MCP‑compatible client (Cline, Cursor, Claude Desktop) can add the server via a marketplace entry or a simple JSON configuration. No need to manage API keys beyond an environment variable.
• Type‑safe operations: The server is written in TypeScript, ensuring that request and response shapes are validated at compile time. This reduces runtime errors when composing complex prompts.
• Customizable filtering: Developers can tune the search parameters on a per‑request basis, enabling use cases such as filtering for earnings reports, regulatory filings, or sentiment‑heavy articles.
• Real‑time freshness: Because the server queries Tavily’s live index, it returns news that is often less than a minute old, which is critical for time‑sensitive trading decisions.

Typical use cases include:

• A financial analyst asking an assistant to “summarize the latest earnings news for Tesla” and receiving a concise, up‑to‑date briefing.
• An automated portfolio manager that triggers rebalancing when a company’s news score drops below a threshold.
• A personal finance chatbot that keeps users informed about significant events affecting their holdings.

Integration into an AI workflow is straightforward: the assistant invokes a tool call to with the desired parameters, receives the structured response, and can then embed the headlines into a natural language summary or feed them into downstream analytics. Because MCP supports two‑way communication, the assistant can also ask for deeper dives or domain‑specific follow‑ups without leaving the conversational context.

Overall, the Search Stock News MCP Server turns raw news data into a first‑class AI resource, enabling developers to build richer, more responsive financial applications with minimal effort.