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Snowflake MCP

Snowflake MCP is an official managed Model Context Protocol server that lets AI agents securely discover and invoke tools like Cortex Analyst, Cortex Search, and Cortex Agents directly against your Snowflake data without deploying extra infrastructure.

What is Snowflake MCP?

Snowflake MCP (Model Context Protocol server) is Snowflake's official implementation of the open-source Model Context Protocol (MCP). It provides a standardized, secure interface for AI agents and applications to discover and call tools that interact with data stored in Snowflake.

Instead of building custom integrations, AI agents (such as those in Cursor, Anthropic Claude, CrewAI, or LangChain) can connect to a managed MCP endpoint hosted by Snowflake and gain access to powerful tools like Cortex Analyst (natural language to SQL), Cortex Search (semantic search over unstructured data), Cortex Agents, custom SQL execution, and more.

Features

  • Fully managed — No infrastructure to deploy or maintain; runs natively inside your Snowflake account.
  • Tool discovery — MCP clients can list available tools dynamically (Cortex Analyst, Cortex Search, custom tools, SQL).
  • Secure authentication — Uses Snowflake's native security model, role-based access, and programmatic access tokens.
  • Enterprise governance — Tools inherit your existing Snowflake policies, row-level security, and data governance.
  • Open standard compliance — Supports the latest MCP revision (2025-11-25) for broad compatibility with agent frameworks.
  • Open-source option — GitHub repo (Snowflake-Labs/mcp) for self-hosted or customized deployments with additional capabilities like object management and semantic views.

Use Cases

  • Agentic analytics — Let AI agents answer business questions in natural language by querying structured data via Cortex Analyst.
  • Semantic search over documents — Enable RAG-style workflows with Cortex Search on unstructured data stored in Snowflake.
  • Multi-tool orchestration — Combine Cortex Analyst, Search, and custom tools in complex agent workflows.
  • Integration with coding agents — Connect Cursor, Claude Desktop, or GitHub Copilot to your Snowflake data for context-aware data engineering and analysis.
  • Cross-platform agents — Use with Amazon Bedrock AgentCore, LangChain, or other MCP-compatible hosts.

How It Works

  1. Create an MCP server object in Snowflake using SQL (specifying which tools to expose).
  2. Generate a programmatic access token for authentication.
  3. Configure your AI agent or MCP client with the server URL.
  4. The agent discovers available tools and invokes them securely to retrieve data or execute actions.

The managed version eliminates the need to run your own server, while the open-source version offers more flexibility for advanced customizations.

Getting Started

Refer to the official Snowflake documentation for setup instructions, including SQL examples to create the MCP server and quickstarts for integrating with popular agent frameworks.

The open-source implementation is available at https://github.com/Snowflake-Labs/mcp for developers who need additional control.

Snowflake MCP significantly lowers the barrier to building secure, production-grade data agents by leveraging a unified open protocol.

Tags

mcpsnowflakecortexai-agentdata-tool

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