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Snowflake MCP Server for Mastra AIGive Mastra AI instant access to 11 tools to Cancel Sql, Describe Table, Execute Sql, and more

Built by Vinkius GDPR 11 Tools SDK

Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Snowflake through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.

Ask AI about this App Connector for Mastra AI

The Snowflake app connector for Mastra AI is a standout in the Industry Titans category — giving your AI agent 11 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

typescript
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";

async function main() {
  // Your Vinkius token. get it at cloud.vinkius.com
  const mcpClient = await createMCPClient({
    servers: {
      "snowflake-alternative": {
        url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
      },
    },
  });

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "Snowflake Agent",
    instructions:
      "You help users interact with Snowflake " +
      "using 11 tools.",
    model: openai("gpt-4o"),
    tools,
  });

  const result = await agent.generate(
    "What can I do with Snowflake?"
  );
  console.log(result.text);
}

main();
Snowflake
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High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Snowflake MCP Server

Connect your Snowflake account to any AI agent to automate your data cloud operations and analytical workflows. Snowflake provides a premier platform for data warehousing and analysis, and this integration allows you to execute SQL statements, browse database schemas, and monitor session contexts through natural conversation.

Mastra's agent abstraction provides a clean separation between LLM logic and Snowflake tool infrastructure. Connect 11 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.

What you can do

  • SQL Query Orchestration — Execute any SQL statement programmatically and retrieve real-time data results for immediate analysis.
  • Database & Schema Oversight — List and search through databases, schemas, and tables to maintain a clear overview of your data architecture directly from the AI interface.
  • Warehouse & Resource Control — Access and monitor available warehouses and user roles to ensure your analytical environment is properly configured.
  • Metadata Intelligence — Describe table structures and retrieve session context metadata via natural language commands to facilitate data exploration.
  • Operational Monitoring — Track statement execution status and cancel long-running queries to ensure your data cloud resources are used efficiently.

The Snowflake MCP Server exposes 11 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 11 Snowflake tools available for Mastra AI

When Mastra AI connects to Snowflake through Vinkius, your AI agent gets direct access to every tool listed below — spanning sql-query, data-warehousing, cloud-data, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

cancel_sql

Cancel a running SQL statement

describe_table

Get table schema details

execute_sql

Returns the first partition of results or a handle for long-running queries. Execute a SQL statement in Snowflake

get_session_context

Get current session context

get_statement_status

Check the status of a SQL statement

list_databases

List all accessible databases

list_roles

List security roles

list_schemas

List schemas in a database

list_tables

List tables in a schema or database

list_users

List Snowflake users

list_warehouses

List compute warehouses

Connect Snowflake to Mastra AI via MCP

Follow these steps to wire Snowflake into Mastra AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.ts and run with npx tsx agent.ts
04

Explore tools

Mastra discovers 11 tools from Snowflake via MCP

Why Use Mastra AI with the Snowflake MCP Server

Mastra AI provides unique advantages when paired with Snowflake through the Model Context Protocol.

01

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Snowflake without touching business code

02

Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation

03

TypeScript-native: full type inference for every Snowflake tool response with IDE autocomplete and compile-time checks

04

One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure

Snowflake + Mastra AI Use Cases

Practical scenarios where Mastra AI combined with the Snowflake MCP Server delivers measurable value.

01

Automated workflows: build multi-step agents that query Snowflake, process results, and trigger downstream actions in a typed pipeline

02

SaaS integrations: embed Snowflake as a first-class tool in your product's AI features with Mastra's clean agent API

03

Background jobs: schedule Mastra agents to query Snowflake on a cron and store results in your database automatically

04

Multi-agent systems: create specialist agents that collaborate using Snowflake tools alongside other MCP servers

Example Prompts for Snowflake in Mastra AI

Ready-to-use prompts you can give your Mastra AI agent to start working with Snowflake immediately.

01

"List all tables in the 'SALES' schema of the 'PROD' database."

02

"Show me the warehouse usage and query performance metrics for all active Snowflake warehouses."

03

"Run a SQL query to get the top 10 customers by revenue from the sales table this quarter."

Troubleshooting Snowflake MCP Server with Mastra AI

Common issues when connecting Snowflake to Mastra AI through the Vinkius, and how to resolve them.

01

createMCPClient not exported

Install: npm install @mastra/mcp

Snowflake + Mastra AI FAQ

Common questions about integrating Snowflake MCP Server with Mastra AI.

01

How does Mastra AI connect to MCP servers?

Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
02

Can Mastra agents use tools from multiple servers?

Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
03

Does Mastra support workflow orchestration?

Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.