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FactSet Launches First Production-Grade MCP Server for Direct AI Access to Nine Financial Datasets

FactSet debuts the first production-grade MCP server, enabling real-time AI access to nine key financial datasets, enhancing decision-making for enterprises.

FactSet (NYSE:FDS) has launched the industry’s first production-grade model context protocol (MCP) server, providing AI systems with direct, real-time access to its curated financial datasets. Announced on December 16, 2025, this initiative allows enterprises to integrate financial intelligence into AI workflows without the need for intermediaries or custom integrations. The MCP server follows a successful beta phase that included 45 firms and more than 800 institutional users, marking a significant milestone in the application of AI in financial services.

The MCP server initially exposes nine critical datasets, including Fundamentals, Consensus Estimates, Ownership, Global M&A intelligence, Global Pricing, People profiles, Events (both live and historical), Supply Chain insights, and Geographic Revenue Exposure. This direct access is designed to streamline AI operations and enhance the quality of decision-making processes for businesses leveraging FactSet’s data.

John Costigan, Chief Data Officer at FactSet, noted that the launch reflects the company’s client-centric approach, which has enabled it to pioneer the MCP technology. “Backed by APIs already trusted and actively used by hundreds of FactSet’s institutional clients for mission-critical workflows, this MCP solution extends those capabilities to agentic and other enterprise deployments,” he stated. Costigan emphasized that the early feedback from clients highlights the transformative potential of this newly accessible data.

The introduction of the MCP server is particularly relevant as enterprises transition from AI experimentation to deployment. Unlike earlier solutions that relied on demo servers and data warehouses, FactSet’s MCP server facilitates a more efficient integration process by allowing AI models to interact directly with the company’s financial datasets. This eliminates the need for manual data exports or previews, making it a valuable tool for CTOs, CIOs, and other innovation leaders developing AI strategies.

FactSet’s stock closed at $292.03 on the day of the announcement, reflecting a slight decline of 0.15%. The trading volume of 703,102 shares was below the 20-day average of 882,108, indicating that investors may not be positioning themselves significantly ahead of this data launch. Shares are currently trading more than 41% below their 52-week high of $496.9, although they sit about 16.58% above the 52-week low of $250.5.

In the broader market context, several of FactSet’s peers also experienced declines, with TRU down 1.82%, MORN down 1.8%, and CBOE down 2.4%. This reflects a sector-wide trend, albeit without a coordinated momentum move detected by market scanners. While FactSet shares have fluctuated due to various external factors, the recent focus on cloud AI integration and partnerships may bolster its competitive positioning in the sector.

Historically, FactSet has seen mixed stock reactions to its announcements. For instance, a strategic partnership with Arcesium on December 3, 2025, resulted in a modest gain of 0.3%, while news about a dividend declaration on November 6 led to a decline of 2.9%. This pattern indicates that while innovative offerings can generate positive market sentiment, dividend announcements and scheduling can sometimes have the opposite effect.

Looking ahead, the launch of the MCP server aligns with FactSet’s ongoing commitment to enhancing its AI and cloud capabilities. The company is poised to expand its dataset coverage and further integrate AI into its services, potentially driving increased demand for its financial intelligence solutions. With an aggressive roadmap in place, FactSet aims to keep its clients at the forefront of market innovation, emphasizing the importance of real-time data access in an increasingly competitive landscape.

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Marcus Chen
Written By

At AIPressa, my work focuses on analyzing how artificial intelligence is redefining business strategies and traditional business models. I've covered everything from AI adoption in Fortune 500 companies to disruptive startups that are changing the rules of the game. My approach: understanding the real impact of AI on profitability, operational efficiency, and competitive advantage, beyond corporate hype. When I'm not writing about digital transformation, I'm probably analyzing financial reports or studying AI implementation cases that truly moved the needle in business.

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