How to integrate OneUp MCP with Vercel AI SDK v6

This guide walks you through connecting OneUp to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working OneUp agent that can create social posts, upload media, edit scheduled posts, comment on posts, and analyze engagement through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a OneUp account through Composio's OneUp MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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OneUp is a social media management platform for scheduling posts, comments, accounts, media, and analytics. Use it to manage multiple social networks from one place and keep publishing consistent.

27 Tools

Introduction

This guide walks you through connecting OneUp to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working OneUp agent that can create social posts, upload media, edit scheduled posts, comment on posts, and analyze engagement through natural language commands.

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

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

Also integrate OneUp with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainMastra AILlamaIndexCrewAI

TL;DR

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

The OneUp MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your OneUp account. It provides structured and secure access to your social accounts, posts, comments, media, and analytics, so your agent can schedule content, manage conversations, review performance, organize accounts, and discover trending sounds on your behalf.

  • Social post creation and scheduling: Have your agent create text, image, or video posts as drafts, scheduled content, or timeslot posts for selected social accounts.
  • Post management and recovery: Direct your agent to list posts, edit or delete scheduled content, and reschedule failed posts for a future date and time.
  • Comment and review management: Let the agent refresh and review comment threads, publish comments and replies, delete comments, and check Google Business Profile reviews.
  • Social and advertising analytics: Instruct your agent to review account performance, audience demographics, individual content results, and Meta Ads analytics, or request updated analytics across connected accounts.
  • Account and content discovery: Have your agent check connected account health, browse account categories, find Instagram or TikTok trending sounds, and list Pinterest boards or YouTube playlists.

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: ["oneup"],
  });

  const mcpUrl = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to OneUp 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 OneUp-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 OneUp 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 oneup, 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 OneUp 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 OneUp 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: ["oneup"],
  });

  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 oneup, 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 OneUp agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.

Key features of this implementation:

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

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

Supported Tools

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

Comment On Post

Publish a new top-level comment on a social post through a connected OneUp social account.

Create Image Post

Create a scheduled, timeslot, or draft image post for selected OneUp social accounts.

Create Media Upload URL

Create a temporary OneUp media upload URL and return instructions for a separate direct upload.

Create Text Post

Create a scheduled, timeslot, or draft text post for selected OneUp social accounts.

Create Video Post

Create a scheduled, timeslot, or draft video post for selected OneUp social accounts.

Delete Comment

Permanently and irreversibly delete a social-platform comment and its local OneUp record.

Delete Scheduled Post

Permanently and irreversibly delete an unpublished scheduled OneUp post.

Edit Scheduled Post

Replace the content and optionally the title of a scheduled OneUp post.

Get Analytics Overview

Get account-level overview metrics and ranked performance for a connected account on a supported social platform.

Get Audience Demographics

Get audience demographics for a connected Facebook, Instagram, TikTok, or YouTube account for a preset or custom reporting period.

Get Content Analytics

Get per-post, Reel, or Story analytics for a connected account on a supported social platform.

Get Google Business Reviews

Get Google Business Profile reviews and aggregate rating information for a connected account or location.

Get Meta Ads Analytics

Get campaign, ad-set, or individual-ad analytics for a connected Meta Ads account.

List Categories

List OneUp categories used to group connected social accounts.

List Category Accounts

List social accounts assigned to a OneUp category.

List Comment Replies

Fetch child replies for a parent social-platform comment.

List Comment Threads

List social posts with top-level comments and child replies in the requested order, one page at a time.

List Instagram Trending Sounds

Search Instagram trending sounds for a Facebook-connected Instagram Business or Creator account.

List Pinterest Boards

List boards available to a connected Pinterest username for post targeting.

List Posts

List scheduled, published, or failed OneUp posts, one page at a time.

List Social Accounts

List all connected OneUp social accounts and their connection health.

List TikTok Trending Sounds

Get TikTok trending commercial sounds for a documented country, period, genre, and connected TikTok account.

List YouTube Playlists

List playlists for a connected YouTube channel.

Refresh Analytics

Start a background refresh of analytics for all connected social accounts.

Refresh Comments

Start a background refresh of comments from connected social platforms.

Reply To Comment

Publish a direct reply to an existing social-platform comment.

Reschedule Failed Post

Move a failed post back into the schedule at a future date and time.

FRAMEWORKS

How to build OneUp MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use OneUp MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use OneUp MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use OneUp MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use OneUp MCP with Claude Cowork

Codex logo

Codex

Use OneUp MCP with Codex

OpenClaw logo

OpenClaw

Use OneUp MCP with OpenClaw

Hermes logo

Hermes

Use OneUp MCP with Hermes

CLI logo

CLI

Use OneUp MCP with CLI

Google ADK logo

Google ADK

Use OneUp MCP with Google ADK

LangChain logo

LangChain

Use OneUp MCP with LangChain

Mastra AI logo

Mastra AI

Use OneUp MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use OneUp MCP with LlamaIndex

CrewAI logo

CrewAI

Use OneUp MCP with CrewAI

FAQ

Frequently asked questions

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

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

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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