# How to integrate Basin MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Basin MCP with Vercel AI SDK v6", "toolkit": "Basin", "toolkit_slug": "basin", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/basin/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/basin/framework/ai-sdk.md", "updated_at": "2026-05-06T08:02:11.959Z" } ``` ## Introduction This guide walks you through connecting Basin to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Basin agent that can create a new form for event signups, delete an old feedback form from project, get details of your contact form through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Basin account through Composio's Basin MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Basin with - [OpenAI Agents SDK](https://composio.dev/toolkits/basin/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/basin/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/basin/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/basin/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/basin/framework/codex) - [OpenClaw](https://composio.dev/toolkits/basin/framework/openclaw) - [Hermes](https://composio.dev/toolkits/basin/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/basin/framework/cli) - [Google ADK](https://composio.dev/toolkits/basin/framework/google-adk) - [LangChain](https://composio.dev/toolkits/basin/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/basin/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/basin/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/basin/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Basin integration - Using Composio's Tool Router to dynamically load and access Basin 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 Basin MCP server, and what's possible with it? The Basin MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Basin account. It provides structured and secure access to your forms and projects, so your agent can perform actions like creating forms, managing webhooks, organizing projects, and retrieving domain or form details on your behalf. - Instant form creation and management: Ask your agent to set up new forms with custom settings, associate them with projects, or delete forms you no longer need—all without manual coding. - Seamless project organization: Let your agent create new Basin projects to group related forms or delete obsolete projects, keeping your workspace tidy and efficient. - Automated webhook and integration setup: Have your agent add or remove webhooks for specific forms, so submissions are instantly routed to the right endpoints or external services. - Detailed form and account insights: Retrieve rich metadata about any form or get a full list of domains linked to your Basin account, helping you monitor and audit your form infrastructure. - Effortless notification management: Empower your agent to configure notification webhooks, ensuring critical submissions reach your team or external tools in real time. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `BASIN_CREATE_FORM` | Create Form | Tool to create a new form in basin. use when you need to automate form setup with name, timezone, and project association; optionally configure redirect, notifications, or spam protection. | | `BASIN_CREATE_FORM_WEBHOOK` | Create Form Webhook | Tool to create a new webhook for a specific form. use when you need to programmatically add a webhook once you have the form id and callback url confirmed. | | `BASIN_CREATE_NOTIFICATION` | Create Notification | Tool to create a new notification webhook. use when you need to forward form submissions to an external service. | | `BASIN_CREATE_PROJECT` | Create Project | Tool to create a new basin project. use when you need a new organizational container for forms. example: "create a project named marketing leads." | | `BASIN_DELETE_FORM` | Delete Form | Tool to delete a form. use when permanently removing a form after it's no longer needed. ensure the form id is correct; this operation is irreversible. | | `BASIN_DELETE_INTEGRATION` | Delete Integration | Tool to delete a form webhook integration. use when removing an obsolete integration by id. | | `BASIN_DELETE_PROJECT` | Delete Project | Tool to delete a project. use when you need to remove a project after confirming its id. returns the deleted project's details. | | `BASIN_DELETE_WEBHOOK` | Delete Webhook | Tool to delete a specific webhook. use when you need to remove a webhook from a form after confirming its id. | | `BASIN_GET_DOMAINS` | Get Domains | Tool to retrieve a list of all domains associated with the account. use after authentication when you need to display or verify your configured domains in basin. | | `BASIN_GET_FORM_DETAILS` | Get Form Details | Tool to retrieve detailed information about a specific form. use when you have a form id and need its metadata. | | `BASIN_GET_FORMS` | Get Forms | Tool to retrieve a list of all forms. use after authentication to fetch all your forms. | | `BASIN_GET_PROJECT_DETAILS` | Get Project Details | Tool to retrieve detailed information about a specific project. use when you have a project id and need its metadata (name, created at, updated at). | | `BASIN_GET_PROJECTS` | Get Projects | Tool to retrieve a list of all projects. use after authentication to fetch your project inventory. | | `BASIN_GET_SUBMISSIONS` | Get Submissions | Tool to retrieve all submissions for a specific form. use when you need to list entries after obtaining the form id. | | `BASIN_GET_WEBHOOKS` | Get Webhooks | Tool to retrieve all webhooks associated with a specific form. use after obtaining the form id. | | `BASIN_UPDATE_INTEGRATION` | Update Integration | Tool to update a form webhook integration. use to modify settings of an existing integration. | | `BASIN_UPDATE_PROJECT` | Update Project | Tool to update details of an existing project. use when you need to change a project's name after confirming the project id. example: "update project 123 to 'rebrand launch'". | | `BASIN_UPDATE_WEBHOOK` | Update Webhook | Tool to update settings of an existing webhook for a form. use after obtaining the webhook's id. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Basin MCP server is an implementation of the Model Context Protocol that connects your AI agent to Basin. It provides structured and secure access so your agent can perform Basin 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 Basin 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 Basin-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: ["basin"], }); 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 Basin 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 basin, 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 Basin 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: ["basin"], }); 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 basin, 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 Basin 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 Basin MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/basin/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/basin/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/basin/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/basin/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/basin/framework/codex) - [OpenClaw](https://composio.dev/toolkits/basin/framework/openclaw) - [Hermes](https://composio.dev/toolkits/basin/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/basin/framework/cli) - [Google ADK](https://composio.dev/toolkits/basin/framework/google-adk) - [LangChain](https://composio.dev/toolkits/basin/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/basin/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/basin/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/basin/framework/crew-ai) ## Related Toolkits - [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. 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It boosts your favorite tools with actionable intelligence and seamless integration. - [Feathery](https://composio.dev/toolkits/feathery) - Feathery is an AI-powered platform for building dynamic data intake forms with advanced logic. It helps teams automate complex workflows and collect structured data with ease. - [Fillout forms](https://composio.dev/toolkits/fillout_forms) - Fillout forms is an online platform for building and managing forms with a flexible API. It lets you create, distribute, and collect responses from forms with ease. - [Formdesk](https://composio.dev/toolkits/formdesk) - Formdesk is an online form builder for creating and managing professional forms. It's perfect for collecting data, automating workflows, and integrating form submissions with your favorite services. - [Formsite](https://composio.dev/toolkits/formsite) - Formsite lets you build online forms and surveys with drag-and-drop simplicity. 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It streamlines repetitive processes so your business runs smoother, faster, and with fewer manual steps. - [Maintainx](https://composio.dev/toolkits/maintainx) - Maintainx is a cloud-based CMMS for centralizing maintenance data, communication, and workflows. It helps organizations streamline maintenance operations and improve team coordination. - [Make](https://composio.dev/toolkits/make) - Make is an automation platform that connects your favorite apps and services. Build powerful, custom workflows without writing code. - [Ntfy](https://composio.dev/toolkits/ntfy) - Ntfy is a notification service to send push messages to phones or desktops. Instantly deliver alerts and updates to users, devices, or teams. - [Persona](https://composio.dev/toolkits/persona) - Persona offers identity infrastructure to automate user verification and compliance. It helps organizations securely verify users and reduce fraud risk. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Basin MCP? With a standalone Basin MCP server, the agents and LLMs can only access a fixed set of Basin tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Basin 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 Basin tools. ### Can I manage the permissions and scopes for Basin while using Tool Router? Yes, absolutely. You can configure which Basin 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 Basin data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)