# How to integrate Airtable MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Airtable MCP with Vercel AI SDK v6", "toolkit": "Airtable", "toolkit_slug": "airtable", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/airtable/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/airtable/framework/ai-sdk.md", "updated_at": "2026-05-12T10:00:41.159Z" } ``` ## Introduction This guide walks you through connecting Airtable to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Airtable agent that can add new contacts from a signup list, create a project tracking table in workspace, delete outdated records from clients table through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Airtable account through Composio's Airtable MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Airtable with - [ChatGPT](https://composio.dev/toolkits/airtable/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/airtable/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/airtable/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/airtable/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/airtable/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/airtable/framework/codex) - [Cursor](https://composio.dev/toolkits/airtable/framework/cursor) - [VS Code](https://composio.dev/toolkits/airtable/framework/vscode) - [OpenCode](https://composio.dev/toolkits/airtable/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/airtable/framework/openclaw) - [Hermes](https://composio.dev/toolkits/airtable/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/airtable/framework/cli) - [Google ADK](https://composio.dev/toolkits/airtable/framework/google-adk) - [LangChain](https://composio.dev/toolkits/airtable/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/airtable/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/airtable/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/airtable/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Airtable integration - Using Composio's Tool Router to dynamically load and access Airtable 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 Airtable MCP server, and what's possible with it? The Airtable MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Airtable account. It provides structured and secure access to your Airtable bases and tables, so your agent can create records, update fields, manage tables, retrieve schemas, and automate project tracking on your behalf. - Seamless record creation and management: Easily instruct your agent to add new records, create multiple entries at once, or delete outdated information across any Airtable table. - Intuitive table and field customization: Ask your agent to design new tables, add or modify fields, and tailor the structure of your bases for evolving projects and workflows. - Efficient schema discovery: Let your agent fetch detailed schema information, including fields and configurations, to power data-driven automation and analysis. - Collaborative commenting: Have your agent add or remove comments on specific records, making team collaboration and discussion much smoother from anywhere. - Bulk operations for productivity: Enable your agent to perform batch actions like creating or deleting multiple records in one go, saving you time on repetitive data management tasks. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `AIRTABLE_CREATE_BASE` | Create base | Creates a new Airtable base with specified tables and fields within a workspace. | | `AIRTABLE_CREATE_COMMENT` | Create Comment | Tool to create a comment on a specific Airtable record. Use when adding comments to records, mentioning collaborators using @[userId] syntax, or creating threaded comment replies. Supports optional parentCommentId for threaded conversations. | | `AIRTABLE_CREATE_FIELD` | Create Field | Creates a new field within a specified table in an Airtable base. | | `AIRTABLE_CREATE_RECORD_FROM_NATURAL_LANGUAGE` | Create Record From Natural Language | Creates a new record in an Airtable table from a natural language description. Fetches the table schema, uses an LLM to generate the correct field payload, and creates the record with typecast enabled for automatic type conversion. | | `AIRTABLE_CREATE_RECORDS` | Create records | Tool to create multiple records (up to 10) in a specified Airtable table. Use when you need to add new rows to a table with field values. Rate limit: 5 requests per second per base. | | `AIRTABLE_CREATE_TABLE` | Create table | Creates a new table within a specified existing Airtable base, allowing definition of its name, description, and field structure. | | `AIRTABLE_DELETE_COMMENT` | Delete Comment | Tool to delete a comment from a record in an Airtable table. Use when you need to remove an existing comment. Non-admin users can only delete their own comments; Enterprise Admins can delete any comment. | | `AIRTABLE_DELETE_MULTIPLE_RECORDS` | Delete multiple records | Tool to delete up to 10 specified records from a table within an Airtable base. Use when you need to remove multiple records in a single operation. | | `AIRTABLE_DELETE_RECORD` | Delete Record | Permanently deletes a specific record from an existing table within an existing Airtable base. | | `AIRTABLE_GET_BASE_SCHEMA` | Get Base Schema | Retrieves the detailed schema for a specified Airtable base, including its tables, fields, field types, and configurations, using the `baseId`. | | `AIRTABLE_GET_RECORD` | Get Record | Retrieves a specific record from an Airtable table by its record ID. Requires a known, valid record ID obtained from listing records or another API call - this tool cannot search or list records. Use the list records tool to find record IDs. Empty field values are not returned in the response. | | `AIRTABLE_GET_USER_INFO` | Get user information | Retrieves information, such as ID and permission scopes, for the currently authenticated Airtable user from the `/meta/whoami` endpoint. | | `AIRTABLE_LIST_BASES` | List bases | Retrieves all Airtable bases accessible to the authenticated user, which may include an 'offset' for pagination. | | `AIRTABLE_LIST_COMMENTS` | List Comments | Tool to list comments on a specific Airtable record. Use when retrieving comments for a record, with optional pagination support for large comment threads. | | `AIRTABLE_LIST_RECORDS` | List records | Tool to list records from an Airtable table with filtering, sorting, and pagination. Use when you need to retrieve multiple records from a table with optional query parameters. | | `AIRTABLE_UPDATE_COMMENT` | Update Comment | Tool to update an existing comment on a specific Airtable record. Use when modifying comment text or updating user mentions using @[userId] syntax. API users can only update comments they have created. | | `AIRTABLE_UPDATE_FIELD` | Update Field | Updates a field's name or description in an Airtable table. Use this action to modify field metadata without changing the field's type or options. At least one of 'name' or 'description' must be provided. | | `AIRTABLE_UPDATE_MULTIPLE_RECORDS` | Update multiple records | Tool to update up to 10 records in an Airtable table with selective field modifications. Use when you need to modify multiple existing records or perform upsert operations. Updates are not performed atomically. | | `AIRTABLE_UPDATE_MULTIPLE_RECORDS_PUT` | Update multiple records (PUT) | Tool to destructively update multiple records in Airtable using PUT, clearing unspecified fields. Use when you need to fully replace record data or perform upsert operations. Supports up to 10 records per request. | | `AIRTABLE_UPDATE_RECORD` | Update record | Modifies specified fields of an existing record in an Airtable base and table; the base, table, and record must exist. | | `AIRTABLE_UPDATE_RECORD_PUT` | Update record (PUT) | Updates an existing record in an Airtable base using PUT method. Use when you want to replace all field values, clearing any unspecified fields. For partial updates that preserve unspecified fields, use the PATCH-based update action instead. | | `AIRTABLE_UPDATE_TABLE` | Update Table | Updates the name, description, and/or date dependency settings of a table in Airtable. Use this action to modify table metadata without changing the table's fields or views. At least one of 'name', 'description', or 'dateDependencySettings' must be provided. | | `AIRTABLE_UPLOAD_ATTACHMENT` | Upload attachment | Uploads a file attachment to a specified field in an Airtable record. Use when you need to add a file to an attachment field. The file must be provided as a base64-encoded string. | ## Supported Triggers | Trigger slug | Name | Description | |---|---|---| | `AIRTABLE_BASE_METADATA_CHANGED_TRIGGER` | Base Metadata Changed | Triggers when an existing Airtable base changes its name or permission level. | | `AIRTABLE_BASE_SCHEMA_CHANGED_TRIGGER` | Base Schema Changed | Triggers when tables, fields, or views change in an Airtable base. | | `AIRTABLE_USER_PROFILE_CHANGED_TRIGGER` | User Profile Changed | Triggers when the connected Airtable user's profile information changes. | | `AIRTABLE_VIEW_CREATED_TRIGGER` | View Created | Triggers when a new view is created in an Airtable base. | | `AIRTABLE_VIEW_DELETED_TRIGGER` | View Deleted | Triggers when a previously known Airtable view is deleted. | | `AIRTABLE_VIEW_METADATA_CHANGED_TRIGGER` | View Metadata Changed | Triggers when an Airtable view changes its name or type. | ## Creating MCP Server - Stand-alone vs Composio SDK The Airtable MCP server is an implementation of the Model Context Protocol that connects your AI agent to Airtable. It provides structured and secure access so your agent can perform Airtable 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 Airtable 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 Airtable-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: ["airtable"], }); 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 Airtable 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 airtable, 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 Airtable 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: ["airtable"], }); 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 airtable, 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 Airtable 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 Airtable MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/airtable/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/airtable/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/airtable/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/airtable/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/airtable/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/airtable/framework/codex) - [Cursor](https://composio.dev/toolkits/airtable/framework/cursor) - [VS Code](https://composio.dev/toolkits/airtable/framework/vscode) - [OpenCode](https://composio.dev/toolkits/airtable/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/airtable/framework/openclaw) - [Hermes](https://composio.dev/toolkits/airtable/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/airtable/framework/cli) - [Google ADK](https://composio.dev/toolkits/airtable/framework/google-adk) - [LangChain](https://composio.dev/toolkits/airtable/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/airtable/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/airtable/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/airtable/framework/crew-ai) ## Related Toolkits - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place. - [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place. - [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place. - [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives. - [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions. - [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date. - [Breeze](https://composio.dev/toolkits/breeze) - Breeze is a project management platform designed to help teams plan, track, and collaborate on projects. It streamlines workflows and keeps everyone on the same page. - [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes. - [Canny](https://composio.dev/toolkits/canny) - Canny is a platform for managing customer feedback and feature requests. It helps teams prioritize product decisions based on real user insights. - [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Airtable MCP? With a standalone Airtable MCP server, the agents and LLMs can only access a fixed set of Airtable tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Airtable 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 Airtable tools. ### Can I manage the permissions and scopes for Airtable while using Tool Router? Yes, absolutely. You can configure which Airtable 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 Airtable data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)