How to integrate Notion MCP with Vercel AI SDK v6

This guide walks you through connecting Notion to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Notion agent that can add meeting notes to project wiki page, create a new task database for q3, archive completed sprint summary pages through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Notion account through Composio's Notion MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.

45 Tools13 Triggers

Introduction

This guide walks you through connecting Notion to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Notion agent that can add meeting notes to project wiki page, create a new task database for q3, archive completed sprint summary pages through natural language commands.

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

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

Also integrate Notion with

TL;DR

Here's what you'll learn:
  • How to set up and configure a Vercel AI SDK agent with Notion integration
  • Using Composio's Tool Router to dynamically load and access Notion 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 Notion MCP server, and what's possible with it?

The Notion MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Notion account. It provides structured and secure access to your notes, docs, wikis, and tasks, so your agent can perform actions like creating pages, managing databases, adding content, commenting, and organizing your Notion workspace for you.

  • Bulk content creation and formatting: Let your agent efficiently add and format multiple blocks of text, lists, or markdown content to Notion pages in one go.
  • Automated page and database management: Have your agent create new pages, duplicate existing ones, or set up entire databases with custom properties—no manual setup required.
  • Smart commenting and collaboration: Enable your agent to add comments to pages or discussion threads, making real-time collaboration smoother.
  • Workspace organization and cleanup: Ask your agent to archive, delete, or restore pages and blocks, keeping your workspace tidy and up to date.
  • Deep block and structure retrieval: Direct your agent to fetch metadata, list child blocks, or dig into nested content for analysis, reporting, or workflow automation.

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:

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

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before you begin, make sure you have:
  • Node.js and npm installed
  • A Composio account with API key
  • An OpenAI API key
2

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.
3

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
4

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
5

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
6

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: ["notion"],
  });

  const mcpUrl = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Notion 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 Notion-related tools through the MCP protocol
7

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 Notion tools that the agent can use
8

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 notion, 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
9

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 Notion 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 Notion 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: ["notion"],
  });

  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 notion, 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 Notion 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 & TRIGGERS

Supported Tools and Triggers

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

Add multiple content blocks (bulk, user-friendly)

Bulk-add content blocks to Notion.

Append code blocks (code, quote, equation)

Append code and technical blocks (code, quote, equation) to a Notion page.

Append layout blocks (divider, TOC, columns)

Append layout blocks (divider, TOC, breadcrumb, columns) to a Notion page.

Append media blocks (image, video, audio, files)

Append media blocks (image, video, audio, file, pdf, embed, bookmark) to a Notion page.

Append table blocks

Append table blocks to a Notion page.

Append task blocks (to-do, toggle, callout)

Append task blocks (to-do, toggle, callout) to a Notion page or block.

Append text blocks (paragraphs, headings, lists)

Append text blocks (paragraphs, headings, lists) to a Notion page.

Archive Notion Page

Archives (moves to trash) or unarchives (restores from trash) a specified Notion page.

Create comment

Adds a comment to a Notion page (via `parent_page_id`) OR to an existing discussion thread (via `discussion_id`); cannot create new discussion threads on specific blocks (inline comments).

Create Notion Database

Creates a new Notion database as a subpage under a specified parent page with a defined properties schema.

Create Notion file upload

Tool to create a Notion FileUpload object and retrieve an upload URL.

Create Notion page

Creates a new page in a Notion workspace under a specified parent page or database.

Delete a block

Archives a Notion block, page, or database using its ID, which sets its 'archived' property to true (like moving to "Trash" in the UI) and allows it to be restored later.

Duplicate page

Duplicates a Notion page, including all its content, properties, and nested blocks, under a specified parent page or workspace.

Fetch All Notion Block Contents

Tool to fetch all child blocks for a given Notion block.

Fetch Notion Block Children

Retrieves a paginated list of direct, first-level child block objects along with contents for a given parent Notion block or page ID; use block IDs from the response for subsequent calls to access deeply nested content.

Fetch Notion block metadata

Fetches metadata for a Notion block (including pages, which are special blocks) using its UUID.

Fetch comments

Fetches unresolved comments for a specified Notion block or page ID.

Fetch Notion Data

Fetches Notion items (pages and/or databases) from the Notion workspace, use this to get minimal data about the items in the workspace with a query or list all items in the workspace with minimal data

Fetch Database

Fetches a Notion database's structural metadata (properties, title, etc.

Fetch database row

Retrieves a Notion database row's properties and metadata; use fetch_block_contents for page content blocks.

Get about user

Retrieves detailed information about a specific Notion user, such as their name, avatar, and email, based on their unique user ID.

Get page markdown

Retrieve a Notion page's full content rendered as Notion-flavored Markdown in a single API call.

Get page property

Call this to get a specific property from a Notion page when you have a valid `page_id` and `property_id`; handles pagination for properties returning multiple items.

Insert row database

Creates a new page (row) in a specified Notion database.

Insert Row From Natural Language

Creates a new row (page) in a Notion database from a natural language description.

List data source templates

Tool to list all templates for a Notion data source.

List Notion file uploads

Tool to retrieve file uploads for the current bot integration, sorted by most recent first.

List users

Retrieves a paginated list of users (excluding guests) from the Notion workspace; the number of users returned per page may be less than the requested `page_size`.

Move Page

Tool to move a Notion page to a new parent (page or database).

Query database

Queries a Notion database to retrieve pages (rows).

Query database with filter

Tool to query a Notion database with server-side filtering, sorting, and pagination.

Query data source

Tool to query a Notion data source.

Replace page content (with backup)

Safely replaces a page's child blocks by optionally backing up current content, deleting existing children, then appending new children in batches.

Retrieve Comment

Tool to retrieve a specific comment by its ID.

Retrieve Database Property

Tool to retrieve a specific property object of a Notion database.

Retrieve Notion file upload

Tool to retrieve details of a Notion File Upload object by its identifier.

Retrieve page

Retrieve a Notion page's properties/metadata (not block content) by page_id.

Search Notion pages and databases

Searches Notion pages and databases by title.

Send file upload

Tool to transmit file contents to Notion for a file upload object.

Update block

Updates existing Notion block's text content.

Update Page

Update page properties, icon, cover, or archive status.

Update Database Row (Page)

Updates a specific row/page within a Notion database by its page UUID (row_id).

Update database schema

Updates an existing Notion database's schema including title, description, and/or properties (columns).

Upsert database rows

Tool to upsert rows in a Notion database by querying for existing rows and creating or updating them.

FAQ

Frequently asked questions

With a standalone Notion MCP server, the agents and LLMs can only access a fixed set of Notion tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Notion 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 Notion tools.

Yes, absolutely. You can configure which Notion 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 Notion data and credentials are handled as safely as possible.

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