AI & ML

MCP Servers on Snowflake Unify and Extend Data Agents

In 2024, Anthropic open sourced the Model Context Protocol (MCP), a standard that enables AI agents to securely interact with enterprise systems where data resides, such as content repositories, business applications, development environments and databases. This allows enterprise businesses to reduce the integration challenges of manual workflows, thereby delivering outcomes from models more quickly. Since then, MCP servers have become foundational for agentic applications, providing a consistent and secure mechanism for invoking tools and retrieving data.

To accelerate enterprise adoption, Snowflake has released open source resources that simplify the creation of MCP servers connected to Snowflake services. With minimal setup, specifying services in a configuration file and authenticating via a programmatic access token, organizations can launch MCP servers that give access to Snowflake Cortex Analyst and Cortex Search capabilities to AI agents. Once configured, MCP clients can dynamically route requests to the appropriate MCP server, whether it’s Cortex Search, Cortex Analyst or other configured options, to complete various tasks. Snowflake has additionally published a quickstart guide for building an MCP server for Cortex Agents, which act as orchestration layers capable of planning, executing and refining multi-step workflows across structured and unstructured data sources. 

Cortex Agents specialize in executing complex data tasks by coordinating across multiple tools. These agents can reason, choose the right tool for the task and iteratively reflect on intermediate outputs, delivering high-quality, end-to-end task execution. By registering a Cortex Agents MCP server, organizations can support multi-agent interactions where the MCP client intelligently selects the appropriate agent based on task complexity.

Bring AI-ready data to your agents

The open source Snowflake MCP servers allow AI agents to interact with data stored in Snowflake using unified, standards-based interfaces. This extends agent capabilities beyond simple queries to more complex retrieval, summarization and analysis workflows, directly within the governed data platform.

Benefits of MCP servers 

Enterprises can take advantage of MCP servers on Snowflake in several ways:

  • Extend data access for agents: MCP servers bring a unified set of data retrieval tools to your agent, expanding its ability to accomplish data retrieval and question-answering tasks on Snowflake data.

  • Retrieval from third-party data: MCP servers also extend beyond internal data. Through Snowlake’s data sharing and Marketplace capabilities, agents can retrieve third-party data securely and seamlessly.

For structured data, the recent introduction of Semantic Model sharing (currently in private preview) allows easy integration of AI-ready data sets, both from internal data producers and external partners such as CARTO and Cotality.

For unstructured data, Cortex Search provides natural language search capabilities across large volumes of documents, PDFs, emails and notes. It indexes unstructured content stored in Snowflake, enabling agents to deliver precise, context-rich responses.

In addition, Cortex Knowledge Extensions available in Snowflake Marketplace allow agents to securely retrieve proprietary content from trusted third-party providers while maintaining proper attribution and intellectual property protection. This includes premium content from The Associated Press, USA TODAY, Washington Post, CB Insights, Packt and more.

Why use MCP servers on Snowflake

Snowflake Cortex AI offers a unified platform for processing and retrieval of both structured and unstructured data with high accuracy out of the box. End-to-end unified governance, from ingestion to application, enables teams to deliver a new wave of data agents. Now with MCP servers on Snowflake, customers can build scalable enterprise-grade applications while maintaining access and privacy controls. 

The key benefits of an MCP server on Snowflake are:

  • Standardized integration: Support for MCP on Snowflake offers a unified interface for tool invocation, eliminating the need for brittle, point-to-point connectors and allowing interoperability across vendors and AI assistants. By doing this, enterprises can get insights from their data on Snowflake.

  • Accelerated AI use case development: Multi-step tasks such as report generation, dashboard creation and document enrichment can be automated using MCP on Snowflake and Cortex Agents, without requiring custom connectors or manual intervention.

  • Authentication, access and governance: The robust authentication support on Snowfake can now be extended for MCP. All data retrieval occurs within the Snowflake account, streamlining observability, access control and compliance workflows.

Enterprise use cases with MCP

MCP servers are already being used in popular tools such as Claude and goose, enabling conversational interfaces for enterprise data. Developers are also integrating them into environments such as Cursor and Copilot to enhance coding workflows with intelligent, data-driven assistance.

Snowflake managed MCP servers are coming soon to Cortex AI

Snowflake Cortex AI MCP servers are on the way. The managed MCP servers will enable agents to remotely and securely retrieve data from Snowflake accounts without the need to deploy your own server infrastructure. MCP is revolutionizing AI interoperability by providing a standardized framework for integrating AI models with external tools! It is poised to become the default protocol for agent communication with tools and resources. 

Start exploring Cortex AI today and enable your teams to build next-generation applications that drive productivity and innovation. 


Related resources

  1. Try Cortex Agents: Build your first Cortex Agent.

  2. Set up your own open source MCP server: Check out our quickstart guide.

  3. Reach out for a preview sign-up of the Cortex AI MCP server.

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