ZoomInfo Launches MCP Integration With Notion Through GTM.AI

The connection includes enterprise access controls, permissioning, data lineage and audit logging.

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VANCOUVER, Wash.--(BUSINESS WIRE)-- ZoomInfo (NASDAQ: GTM), the all-in-one AI GTM platform, today announced an MCP integration with Notion that brings ZoomInfo GTM Intelligence into Notion AI. ZoomInfo customers on Notion Business and Enterprise plans can connect ZoomInfo as a connector in Notion AI chat and get answers grounded in ZoomInfo company and contact data while they work in Notion.

The integration runs on GTM.AI, ZoomInfo's headless GTM context layer. GTM.AI connects ZoomInfo's data and agentic orchestration through an API and a Model Context Protocol (MCP) server, so platforms such as Notion can connect to ZoomInfo without building their own data layer. Notion AI reaches ZoomInfo through the same MCP connection that powers ZoomInfo's other partner and developer integrations.

ZoomInfo's GTM Context Graph covers about 100 million companies, 500 million contacts, and billions of signals. Identity resolution connects those records across sources, so a question about an account or a buying committee returns one consistent answer, whether it is asked inside Notion or in another connected tool. Use the MCP with Notion to help build out your campaign audience, size out your TAM, and much more.

The capabilities for the connection between Notion and ZoomInfo include being able to pull real-time context like firmographic data, and buying signals directly into your Notion notes, project docs and AI prompts without switching between apps. This can help to prep for account or customer calls and to create strategy documents for unified go-to-market planning.

“Notion AI is most useful when it can reach the context teams rely on every day,” said David Rosenberg, Head of Ecosystem at Notion. “Through ZoomInfo’s MCP connector, go-to-market teams can ask Notion AI about any account or buying committee and get answers grounded in ZoomInfo’s data. This partnership is a strong example of how open connections make Notion AI more useful for the work our customers already do.”

Enterprise controls apply to the connection, including access control, permissioning, data lineage, and audit logging.

The Notion launch adds to a growing set of places where ZoomInfo GTM Intelligence is available through MCP. Each connector draws on the same GTM Context Graph, so customers get consistent records wherever they work.

The Notion connector is available to ZoomInfo customers on any ZoomInfo plan whose Notion workspace is on a Business or Enterprise plan. Notion workspace admins manage which connections are available to users.

Core ZoomInfo tools, including contact search and enrichment, work on all ZoomInfo plans; some advanced tools require additional entitlements or credits. Customers can find setup steps and the connector listing at zoominfo.com/integrations/notion. ZoomInfo's broader catalog of partner integrations, including its MCP and API options for developers, is available at zoominfo.com/integrations.

About ZoomInfo

ZoomInfo (NASDAQ: GTM), the all-in-one AI GTM platform, enables sales, marketing, and customer success teams to execute their go-to-market strategy with confidence. Powered by the industry's most comprehensive B2B data, including more than 100 million companies, 500 million contacts, and billions of signals, ZoomInfo delivers the intelligence, automation, and integrations that modern revenue teams need to identify, engage, and convert their best buyers.

GTM.AI is a headless layer that connects to ZoomInfo’s GTM Context Graph. It is the API and Model Context Protocol home for AI agents, powering integrations across Salesforce, HubSpot, Microsoft, Anthropic, OpenAI, Perplexity, and dozens more.

Learn more at zoominfo.com and gtm.ai.

View source version on businesswire.com: https://www.businesswire.com/news/home/20261103978960/en/

Media contact: Public Relations Team, ZoomInfo: PR@zoominfo.com

Source: ZoomInfo

Key Terms

model context protocol (mcp) technical

The Model Context Protocol (MCP) is a system that helps financial models understand and share information about market conditions and data. It’s like a common language that ensures different tools and models work together smoothly, making predictions and decisions more accurate and consistent.

api technical

An API, or Application Programming Interface, is a set of rules that allows different software programs to communicate and work together smoothly, much like a waiter translating your order into the kitchen and then bringing your meal back. For investors, APIs are important because they enable real-time access to financial data, trading systems, and other digital services, making it easier to make informed decisions quickly and efficiently.

firmographic data technical

Firmographic data is basic descriptive information about a business—such as industry, size, revenue band, number of employees, location, and ownership type—that acts like demographic data does for people. For investors it’s a quick way to map market segments, compare peers, estimate addressable market and operational risk, and prioritize targets or customers, much like a map and profile help a shopper decide which neighborhoods and stores to visit.

identity resolution technical

Identity resolution is the process of stitching together pieces of data—like email addresses, device IDs, purchase history and other signals—so a company can recognize when different interactions belong to the same person. For investors, it matters because better identity resolution improves marketing efficiency, customer measurement and fraud detection, which can raise revenue predictability and reduce compliance risk; think of it as turning scattered puzzle pieces into a single, usable customer portrait.

data lineage technical

Data lineage is a map that shows where a piece of data came from, how it moved and changed, and where it is used — like a package tracking history for information. For investors, clear lineage helps verify that financial metrics, risk models, or product analytics are built on reliable inputs, supports regulatory audits, and reduces the chance that decisions are based on corrupted or misunderstood data.