# How to integrate Snowflake MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Snowflake MCP with Vercel AI SDK v6", "toolkit": "Snowflake", "toolkit_slug": "snowflake", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/snowflake/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/snowflake/framework/ai-sdk.md", "updated_at": "2026-05-12T10:26:42.921Z" } ``` ## 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 a sql query to list today's new users, cancel a long-running data import statement, show all unresolved incidents in snowflake 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. ## Also integrate Snowflake with - [ChatGPT](https://composio.dev/toolkits/snowflake/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/snowflake/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/snowflake/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/snowflake/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/snowflake/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/snowflake/framework/codex) - [Cursor](https://composio.dev/toolkits/snowflake/framework/cursor) - [VS Code](https://composio.dev/toolkits/snowflake/framework/vscode) - [OpenCode](https://composio.dev/toolkits/snowflake/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/snowflake/framework/openclaw) - [Hermes](https://composio.dev/toolkits/snowflake/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/snowflake/framework/cli) - [Google ADK](https://composio.dev/toolkits/snowflake/framework/google-adk) - [LangChain](https://composio.dev/toolkits/snowflake/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/snowflake/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/snowflake/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/snowflake/framework/crew-ai) ## 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 cloud data warehouse, so your agent can run complex SQL queries, monitor system health, check scheduled maintenances, and manage incidents seamlessly—no manual intervention needed. - Automated SQL execution and data retrieval: Direct your agent to execute SQL statements and instantly fetch query results from your data warehouse. - Query management and cancellation: Have your agent monitor and cancel long-running or stuck SQL statements to keep your workflows running smoothly. - Maintenance and system status monitoring: Let your agent check for active, upcoming, or completed scheduled maintenances and get real-time updates on system components. - Incident detection and reporting: Enable your agent to retrieve unresolved incidents and receive summaries of any issues currently affecting your Snowflake environment. - Integration metadata access: Fetch details about catalog integrations and system status rollups so your agent can keep tabs on the overall health of your Snowflake setup. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SNOWFLAKE_CANCEL_STATEMENT_EXECUTION` | Cancel Statement Execution | Cancels the execution of a running SQL statement. Use this action to stop a long-running query. | | `SNOWFLAKE_CHECK_STATEMENT_STATUS` | Check Statement Status | Retrieves the status and results of a previously submitted SQL statement using its statement handle. Use this to poll async queries submitted via SNOWFLAKE_SUBMIT_SQL_STATEMENT; call repeatedly until status is no longer pending. Use SNOWFLAKE_CANCEL_STATEMENT to abort a hanging query. | | `SNOWFLAKE_EXECUTE_SQL` | Execute SQL | Execute SQL statements in Snowflake and retrieve results. Supports SELECT queries for data retrieval, DDL statements (CREATE, ALTER, DROP) for schema management, and DML statements (INSERT, UPDATE, DELETE) for data modification. Returns comprehensive result metadata including column types, row counts, and execution status. Unquoted SQL identifiers are auto-uppercased by Snowflake — use matching case in `database`, `schema_name`, `warehouse`, and `role` parameters to avoid 'object not found' errors. Always apply explicit time-range filters and a LIMIT clause to unbounded SELECT queries to prevent large, slow result sets. | | `SNOWFLAKE_FETCH_CATALOG_INTEGRATION` | Fetch Catalog Integration | Retrieves detailed configuration and metadata for a specific catalog integration. Catalog integrations allow Snowflake to connect to external Apache Iceberg catalogs (AWS Glue, Snowflake Open Catalog/Polaris, or Apache Iceberg REST catalogs) to query Iceberg tables managed by those external systems. | | `SNOWFLAKE_GET_ACTIVE_SCHEDULED_MAINTENANCES` | Get Active Scheduled Maintenances | Retrieves a list of any active scheduled maintenances currently in the In Progress or Verifying state. | | `SNOWFLAKE_GET_ALL_SCHEDULED_MAINTENANCES` | Get All Scheduled Maintenances | Retrieves a list of the 50 most recent scheduled maintenances, including those in the Completed state. | | `SNOWFLAKE_GET_COMPONENT_STATUS` | Get Component Status | Retrieves the status of individual components, each listed with its current status. | | `SNOWFLAKE_GET_STATUS_ROLLUP` | Get Status Rollup | Retrieves the status rollup for the entire page, including indicators and human-readable descriptions of the blended component status. | | `SNOWFLAKE_GET_STATUS_SUMMARY` | Get Status Summary | Retrieves the current status summary from Snowflake's public status page (status.snowflake.com). Returns overall system status, operational status of all regional components (AWS, Azure, GCP regions), any unresolved incidents, and upcoming or in-progress scheduled maintenances. This is a public endpoint that provides global Snowflake service status, not account-specific information. | | `SNOWFLAKE_GET_UNRESOLVED_INCIDENTS` | Get Unresolved Incidents | Retrieves a list of any unresolved incidents from the Snowflake status page. This endpoint returns incidents currently in the Investigating, Identified, or Monitoring state. Returns an empty list if there are no active incidents. This is a public status page API that does not require authentication. | | `SNOWFLAKE_GET_UPCOMING_SCHEDULED_MAINTENANCES` | Get Upcoming Scheduled Maintenances | Retrieves upcoming scheduled maintenances from Snowflake's public status page. This action queries the Snowflake status API to get a list of any scheduled maintenance events that are still in the 'Scheduled' state (not yet started or completed). The response includes maintenance details such as impact level, scheduled time windows, incident updates, and direct links to the maintenance notices. Note: This uses Snowflake's public status API and does not require authentication. | | `SNOWFLAKE_SHOW_DATABASES` | Show Databases | Lists all databases for which you have access privileges. Shows database metadata including name, creation date, owner, retention time, and more. Can filter results and include dropped databases within Time Travel retention period. | | `SNOWFLAKE_SHOW_SCHEMAS` | Show Schemas | Lists all schemas for which you have access privileges. Shows schema metadata including name, creation date, owner, database, retention time, and more. Can filter results and include dropped schemas within Time Travel retention period. | | `SNOWFLAKE_SHOW_TABLES` | Show Tables | Lists all tables for which you have access privileges. Shows table metadata including name, creation date, owner, database, schema, row count, size in bytes, clustering keys, and more. Can filter results and include dropped tables within Time Travel retention period. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Snowflake MCP server is an implementation of the Model Context Protocol that connects your AI agent to Snowflake. It provides structured and secure access so your agent can perform Snowflake operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies 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 ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables 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 ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment 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 ```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, }); ``` ### 5. Create Tool Router session and initialize MCP client 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 ```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; ``` ### 6. Connect to MCP server and retrieve 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 ```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(); ``` ### 7. Initialize conversation and CLI interface 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 ```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(); ``` ### 8. Handle user input and stream responses with real-time tool feedback 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 ```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); }); ``` ## Complete Code ```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. ## How to build Snowflake MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/snowflake/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/snowflake/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/snowflake/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/snowflake/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/snowflake/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/snowflake/framework/codex) - [Cursor](https://composio.dev/toolkits/snowflake/framework/cursor) - [VS Code](https://composio.dev/toolkits/snowflake/framework/vscode) - [OpenCode](https://composio.dev/toolkits/snowflake/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/snowflake/framework/openclaw) - [Hermes](https://composio.dev/toolkits/snowflake/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/snowflake/framework/cli) - [Google ADK](https://composio.dev/toolkits/snowflake/framework/google-adk) - [LangChain](https://composio.dev/toolkits/snowflake/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/snowflake/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/snowflake/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/snowflake/framework/crew-ai) ## Related Toolkits - [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources. - [Tavily](https://composio.dev/toolkits/tavily) - 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](https://composio.dev/toolkits/exa) - 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](https://composio.dev/toolkits/serpapi) - 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. - [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data. - [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights. - [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly. - [Bright Data MCP](https://composio.dev/toolkits/brightdata_mcp) - Bright Data MCP is an AI-powered web scraping and data collection platform. Instantly access public web data in real time with advanced scraping tools. - [Browseai](https://composio.dev/toolkits/browseai) - Browseai is a web automation and data extraction platform that turns any website into an API. It's perfect for monitoring websites and retrieving structured data without manual scraping. - [ClickHouse](https://composio.dev/toolkits/clickhouse) - ClickHouse is an open-source, column-oriented database for real-time analytics and big data processing using SQL. Its lightning-fast query performance makes it ideal for handling large datasets and delivering instant insights. - [Coinmarketcal](https://composio.dev/toolkits/coinmarketcal) - CoinMarketCal is a community-powered crypto calendar for upcoming events, announcements, and releases. It helps traders track market-moving developments and stay ahead in the crypto space. - [Control d](https://composio.dev/toolkits/control_d) - Control d is a customizable DNS filtering and traffic redirection platform. It helps you manage internet access, enforce policies, and monitor usage across devices and networks. - [Databox](https://composio.dev/toolkits/databox) - Databox is a business analytics platform that connects your data from any tool and device. It helps you track KPIs, build dashboards, and discover actionable insights. - [Databricks](https://composio.dev/toolkits/databricks) - Databricks is a unified analytics platform for big data and AI on the lakehouse architecture. It empowers data teams to collaborate, analyze, and build scalable solutions efficiently. - [Datagma](https://composio.dev/toolkits/datagma) - Datagma delivers data intelligence and analytics for business growth and market discovery. Get actionable market insights and track competitors to inform your strategy. - [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment. - [Dovetail](https://composio.dev/toolkits/dovetail) - Dovetail is a research analysis platform for transcript review and insight generation. It helps teams code interviews, analyze feedback, and create actionable research summaries. - [Dub](https://composio.dev/toolkits/dub) - Dub is a short link management platform with analytics and API access. Use it to easily create, manage, and track branded short links for your business. - [Elasticsearch](https://composio.dev/toolkits/elasticsearch) - Elasticsearch is a distributed, RESTful search and analytics engine for all types of data. It delivers fast, scalable search and powerful analytics across massive datasets. - [Fireflies](https://composio.dev/toolkits/fireflies) - Fireflies.ai is an AI-powered meeting assistant that records, transcribes, and analyzes voice conversations. It helps teams capture call notes automatically and search or summarize meetings effortlessly. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Snowflake MCP? 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. ### Can I use Tool Router MCP with Vercel AI SDK v6? 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. ### Can I manage the permissions and scopes for Snowflake while using Tool Router? 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. ### How safe is my data with Composio Tool Router? 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. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)