Use
COMPOSIOFOR YOU
Give Claude, Codex, or any harness secure access to 1500+ tools
CLI
One command to add tools and auth to your coding agent
Build
DEVELOPER PLATFORM
SDKs, tools, and auth for agents and backend apps
MCP GATEWAY
One managed MCP endpoint for all your tools and agents
ENTERPRISE
SSO, governance, and audit controls for deploying agents org-wide
Features
TRIGGERS
Start background agents from events across your connected apps
FIREWALLNEW
Blocks instructions hidden in tool results before your agent reads them
INSTANTNEW
Audio, video, search, browser and data tools, with no keys to manage
OPTIMIZATION
Lower cost per completed task with optimised tools and skills
FOR AGENTS
CLAUDE CODEX OPENCLAW CURSOR HERMES
BUILT FOR
OFFICE WORK SALES MARKETING PRODUCT & DESIGN CUSTOMER SUPPORT ENGINEERING HR & RECRUITING FINANCE & OPS E-COMMERCE CONTENT & MEDIA IT & SECURITY
ALL USE CASES
DOCS

How to integrate Snowflake MCP with Vercel AI SDK v6

Connect Vercel AI SDK v6 to Snowflake MCP. Run a sql query to list today's new users, cancel a long-running data import statement, and more using natural language, with authentication handled for you.

Get started for free Get a demo

Snowflake

Oauth2

Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds.

16 Tools

Managed auth

Connect Snowflake without auth hassles

We manage OAuth, API keys, token refresh, and scopes — you just build.

Book a call

Explore the MCP Gateway

Introduction

This guide walks you through connecting Snowflake to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Snowflake agent that can run SQL statements, check or cancel running queries, list databases and schemas, browse tables, and monitor Snowflake service status through natural language commands.

This guide will help you understand how to give your Vercel AI SDK agent real control over a Snowflake account through Composio's Snowflake MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:

How to set up and configure a Vercel AI SDK agent with Snowflake integration
Using Composio's Tool Router to dynamically load and access Snowflake tools
Creating an MCP client connection using HTTP transport
Building an interactive CLI chat interface with conversation history management
Handling tool calls and results within the Vercel AI SDK framework

What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.

Key features include:

streamText: Core function for streaming responses with real-time tool support
MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
OpenAI Provider: Native integration with OpenAI models

What is the Snowflake MCP server, and what's possible with it?

The Snowflake MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Snowflake account. It provides structured and secure access to your data warehouse and Snowflake service status, so your agent can execute SQL, explore databases and tables, track or cancel statements, inspect catalog integrations, and monitor incidents and maintenance on your behalf.

SQL execution and analysis: Have your agent run SQL statements in Snowflake and retrieve the results for analysis.
Database structure discovery: Let the agent list the databases, schemas, and tables your account can access.
Statement monitoring and control: Direct your agent to check the status and results of submitted SQL statements or cancel a running statement.
Warehouse and catalog administration: Instruct your agent to review the configuration of a catalog integration or permanently drop a warehouse when needed.
Service health monitoring: Have your agent check Snowflake component status, unresolved incidents, and active, recent, or upcoming scheduled maintenance.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS

Prerequisites

Before you begin, make sure you have:

Node.js and npm installed
A Composio account with API key
An OpenAI API key

Getting API Keys for OpenAI and Composio

OpenAI API Key

Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
Keep the API key safe.

Composio API Key

Log in to the Composio dashboard.
Navigate to your API settings and generate a new API key.
Store this key securely as you'll need it for authentication.

Install required dependencies

bash

npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv

First, install the necessary packages for your project.

What you're installing:

@ai-sdk/openai: Vercel AI SDK's OpenAI provider
@ai-sdk/mcp: MCP client for Vercel AI SDK
@composio/core: Composio SDK for tool integration
ai: Core Vercel AI SDK
dotenv: Environment variable management

Set up environment variables

bash

OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here

Create a .env file in your project root.

What's needed:

OPENAI_API_KEY: Your OpenAI API key for GPT model access
COMPOSIO_API_KEY: Your Composio API key for tool access
COMPOSIO_USER_ID: A unique identifier for the user session

Import required modules and validate environment

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

What's happening:

We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
The dotenv/config import automatically loads environment variables
The MCP client import enables connection to Composio's tool server

Create Tool Router session and initialize MCP client

typescript

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["snowflake"],
  });

  const mcpUrl = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Snowflake tools
The create method takes the user ID and specifies which toolkits should be available
The returned mcp object contains the URL and authentication headers needed to connect to the MCP server
This session provides access to all Snowflake-related tools through the MCP protocol

Connect to MCP server and retrieve tools

typescript

const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();

What's happening:

We're creating an MCP client that connects to our Composio Tool Router session via HTTP
The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
The type: "http" is important - Composio requires HTTP transport
tools() retrieves all available Snowflake tools that the agent can use

Initialize conversation and CLI interface

typescript

let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to snowflake, like summarize my last 5 emails, send an email, etc... :)))\n",
);

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

What's happening:

We initialize an empty messages array to maintain conversation history
A readline interface is created to accept user input from the command line
Instructions are displayed to guide the user on how to interact with the agent

Handle user input and stream responses with real-time tool feedback

typescript

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({ role: "user", content: trimmedInput });
  console.log("\nAgent is thinking...\n");

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});

What's happening:

We use streamText instead of generateText to stream responses in real-time
toolChoice: "auto" allows the model to decide when to use Snowflake tools
stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
onStepFinish callback displays which tools are being used in real-time
We iterate through the text stream to create a typewriter effect as the agent responds
The complete response is added to conversation history to maintain context
Errors are caught and displayed with helpful retry suggestions

Complete Code

Here's the complete code to get you started with Snowflake and Vercel AI SDK:

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["snowflake"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to snowflake, like summarize my last 5 emails, send an email, etc... :)))\n",
  );

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
      console.log("\nGoodbye!");
      rl.close();
      process.exit(0);
    }

    if (!trimmedInput) {
      rl.prompt();
      return;
    }

    messages.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});

Conclusion

You've successfully built a Snowflake agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.

Key features of this implementation:

Real-time streaming responses for a better user experience with typewriter effect
Live tool execution feedback showing which tools are being used as the agent works
Dynamic tool loading through Composio's Tool Router with secure authentication
Multi-step tool execution with configurable step limits (up to 10 steps)
Comprehensive error handling for robust agent execution
Conversation history maintenance for context-aware responses

You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

TOOLS

Supported Tools

Every Snowflake action and event your agent gets out of the box.

Cancel Statement Execution

Cancels the execution of a running SQL statement.

Check Statement Status

Checks a submitted SQL statement by handle and retrieves results for a completed statement, optionally for a specified partition.

Drop Warehouse

Drops a Snowflake warehouse by its case-sensitive name.

Execute SQL

Submits SQL statements to Snowflake, including SELECT, DDL, and DML.

Fetch Catalog Integration

Retrieves detailed configuration and metadata for a specific catalog integration.

Get Active Scheduled Maintenances

Retrieves a list of any active scheduled maintenances currently in the In Progress or Verifying state.

Get All Scheduled Maintenances

Retrieves up to 10 of the 50 most recent scheduled maintenances from Snowflake's status page, including completed events.

Get Component Status

Retrieves the status of individual components, each listed with its current status.

Get Status Rollup

Retrieves the status rollup for the entire page, including indicators and human-readable descriptions of the blended component status.

Get Status Summary

Retrieves Snowflake's public status summary, including overall status, component statuses, unresolved incidents, and upcoming or in-progress maintenance.

Get Unresolved Incidents

Retrieves a list of any unresolved incidents from the Snowflake status page.

Get Upcoming Scheduled Maintenances

Retrieves upcoming scheduled maintenances from Snowflake's public status page.

Show Databases

Lists all databases for which you have access privileges.

Show Schemas

Lists all schemas for which you have access privileges.

Show Tables

Lists accessible Snowflake tables in the requested scope, with metadata, filters, and optional dropped-table history.

Validate Credential

Checks Snowflake credentials by submitting a lightweight session query, useful before running other account operations.

FRAMEWORKS

How to build Snowflake MCP Agent with another framework

Claude Code

Use Snowflake MCP with Claude Code

Cursor

Use Snowflake MCP with Cursor

ChatGPT

Use Snowflake MCP with ChatGPT

Claude Cowork

Use Snowflake MCP with Claude Cowork

Antigravity

Use Snowflake MCP with Antigravity

OpenAI Agents SDK

Use Snowflake MCP with OpenAI Agents SDK

Claude Agent SDK

Use Snowflake MCP with Claude Agent SDK

Grok Bot

Use Snowflake MCP with Grok Bot

Muse

Use Snowflake MCP with Muse

Codex

Use Snowflake MCP with Codex

Kimi Code

Use Snowflake MCP with Kimi Code

Grok Build

Use Snowflake MCP with Grok Build

VS Code

Use Snowflake MCP with VS Code

OpenCode

Use Snowflake MCP with OpenCode

OpenClaw

Use Snowflake MCP with OpenClaw

Hermes

Use Snowflake MCP with Hermes

Atomic Agent

Use Snowflake MCP with Atomic Agent

CLI

Use Snowflake MCP with CLI

Google ADK

Use Snowflake MCP with Google ADK

LangChain

Use Snowflake MCP with LangChain

Mastra AI

Use Snowflake MCP with Mastra AI

LlamaIndex

Use Snowflake MCP with LlamaIndex

CrewAI

Use Snowflake MCP with CrewAI

Pydantic AI

Use Snowflake MCP with Pydantic AI

AutoGen

Use Snowflake MCP with AutoGen

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Firecrawl

Api Key

Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.

Tavily

Api Key

Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.

Exa

Api Key

Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.

Serpapi

Api Key

SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.

FAQ

Frequently asked questions

With a standalone Snowflake MCP server, the agents and LLMs can only access a fixed set of Snowflake tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Snowflake and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Vercel AI SDK v6 fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Snowflake tools.

Yes, absolutely. You can configure which Snowflake scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Snowflake data and credentials are handled as safely as possible.

Start with Snowflake.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Snowflake tool your agent needs.Free to start.

Start building

How to integrate Snowflake MCP with Vercel AI SDK v6

Connect Snowflake without auth hassles

Introduction

Also integrate Snowflake with

TL;DR

What is Vercel AI SDK?

What is the Snowflake MCP server, and what's possible with it?

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install required dependencies

Set up environment variables

Import required modules and validate environment

Create Tool Router session and initialize MCP client

Connect to MCP server and retrieve tools

Initialize conversation and CLI interface

Handle user input and stream responses with real-time tool feedback

Complete Code

Conclusion

Supported Tools

How to build Snowflake MCP Agent with another framework

Claude Code

Cursor

ChatGPT

Claude Cowork

Antigravity

OpenAI Agents SDK

Claude Agent SDK

Grok Bot

Muse

Codex

Kimi Code

Grok Build

VS Code

OpenCode

OpenClaw

Hermes

Atomic Agent

CLI

Google ADK

LangChain

Mastra AI

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Firecrawl

Tavily

Exa

Serpapi

Frequently asked questions

What are the differences in Tool Router MCP and Snowflake MCP?+

Can I use Tool Router MCP with Vercel AI SDK v6?+

Can I manage the permissions and scopes for Snowflake while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Snowflake.It takes 30 seconds.