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Snowflake MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 11 tools to Cancel Sql, Describe Table, Execute Sql, and more

Built by Vinkius GDPR 11 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Snowflake through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Use with Your AI Agent

Ask AI about this App Connector for OpenAI Agents SDK

Open in ChatGPT Open in Claude Open in Perplexity

The Snowflake app connector for OpenAI Agents SDK 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

python
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Snowflake Assistant",
            instructions=(
                "You help users interact with Snowflake. "
                "You have access to 11 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Snowflake"
        )
        print(result.final_output)

asyncio.run(main())
Snowflake
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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.

The OpenAI Agents SDK auto-discovers all 11 tools from Snowflake through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Snowflake, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

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 OpenAI Agents SDK 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 OpenAI Agents SDK

When OpenAI Agents SDK 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 OpenAI Agents SDK via MCP

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

01

Install the SDK

Run pip install openai-agents in your Python environment
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Run the script

Save the code above and run it: python agent.py
04

Explore tools

The agent will automatically discover 11 tools from Snowflake

Why Use OpenAI Agents SDK with the Snowflake MCP Server

OpenAI Agents SDK provides unique advantages when paired with Snowflake through the Model Context Protocol.

01

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

02

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

03

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

04

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Snowflake + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Snowflake MCP Server delivers measurable value.

01

Automated workflows: build agents that query Snowflake, process the data, and trigger follow-up actions autonomously

02

Multi-agent orchestration: create specialist agents. one queries Snowflake, another analyzes results, a third generates reports

03

Data enrichment pipelines: stream data through Snowflake tools and transform it with OpenAI models in a single async loop

04

Customer support bots: agents query Snowflake to resolve tickets, look up records, and update statuses without human intervention

Example Prompts for Snowflake in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK

Common issues when connecting Snowflake to OpenAI Agents SDK through the Vinkius, and how to resolve them.

01

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents
02

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Snowflake + OpenAI Agents SDK FAQ

Common questions about integrating Snowflake MCP Server with OpenAI Agents SDK.

01

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.
02

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.
03

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.