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Morningstar

Morningstar

MCP Server

MCP Server: Morningstar

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Updated 25 days ago

About

This repo is currently archived and development on this MCP Server is being done outside this repo

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Morningstar MCP Server

The Morningstar MCP server provides AI assistants with direct access to a rich set of financial data and editorial insights from Morningstar. By exposing two distinct tools—Morningstar Datapoint and Morningstar Articles—the server solves the common developer challenge of retrieving authoritative, up‑to‑date market information and expert analysis within a single, unified workflow. Instead of scattering API calls across multiple providers or parsing HTML pages, developers can rely on a single MCP endpoint to fetch structured data and curated research.

Morningstar Datapoint delivers granular, real‑time metrics for equities and funds. Values such as market capitalization, earnings per share, net asset value, and total return are returned in a consistent format, enabling quick look‑ups for specific securities. This tool is ideal when an assistant needs to answer factual queries—“What was the last closing price of XYZ?” or “How many shares does ABC fund hold?”—without performing additional calculations. The uniform output also simplifies downstream processing, allowing the AI to embed these figures directly into reports or visualizations.

Morningstar Articles opens a gateway to Morningstar’s editorial universe. The tool retrieves research, thematic analyses, and investment strategy articles written by seasoned analysts. It is tailored for questions that require context or opinion—such as “What are the latest trends in sustainable investing?” or “How does Morningstar evaluate sector performance?” By returning vetted, methodology‑driven content, the server ensures that assistants provide insights grounded in credible research rather than raw data alone.

Developers can integrate these tools into conversational agents, financial dashboards, or automated portfolio managers. For example, a chatbot could first use Datapoint to confirm a stock’s current price and then consult Articles to recommend an investment thesis, all within the same turn. The server’s authentication model—requiring a dedicated token and endpoint per account—keeps data usage secure while granting fine‑grained control over which resources a client can access.

What sets the Morningstar MCP server apart is its dual focus on quantitative metrics and qualitative analysis. While many data providers offer price feeds, few combine them with editorial expertise in a single protocol interface. This combination empowers developers to build richer, more informed AI experiences that can answer both “what is” and “why it matters” questions with a single, seamless integration.