How to integrate Linkedin Ads MCP with Vercel AI SDK v6

This guide walks you through connecting Linkedin Ads to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Linkedin Ads agent that can list active campaigns with daily spend, compare ad performance by campaign objective, create report for sponsored content clicks through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Linkedin Ads account through Composio's Linkedin Ads MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Linkedin Ads is LinkedIn's marketing platform for creating, managing, and measuring paid campaigns across LinkedIn. It helps teams reach professional audiences with precise targeting, campaign analytics, and sponsored content tools.

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Introduction

This guide walks you through connecting Linkedin Ads to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Linkedin Ads agent that can list active campaigns with daily spend, compare ad performance by campaign objective, create report for sponsored content clicks through natural language commands.

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

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

Also integrate Linkedin Ads 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 Linkedin Ads integration
  • Using Composio's Tool Router to dynamically load and access Linkedin Ads 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 Linkedin Ads MCP server, and what's possible with it?

The Linkedin Ads MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Linkedin Ads account. It provides structured and secure access to your ad accounts, campaign groups, creatives, targeting data, lead forms, and organization content, so your agent can search ad accounts, inspect campaigns, create lead forms, review targeting options, and forecast ad inventory on your behalf.

  • Ad account discovery and creation: Have your agent search existing ad accounts by status or type, retrieve account details, or create a new ad account.
  • Campaign and creative review: Let the agent retrieve campaign group details and search your LinkedIn Ads creatives using available filters.
  • Audience targeting and forecasting: Direct your agent to explore targeting options such as industries, locations, seniorities, job functions, and skills, then check ad inventory forecasts for your planned audience, budget, and bid.
  • Lead forms and conversion tracking: Instruct your agent to create or retrieve lead generation forms and list the conversion rules connected to an ad account.
  • Organization content and audience data: Have your agent find LinkedIn organizations, review posting permissions, list organization posts, and inspect available audience segments.

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: ["linkedin_ads"],
  });

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

  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 linkedin_ads, 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 Linkedin Ads 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 Linkedin Ads action and event your agent gets out of the box.

Create Ad Account

Tool to create a new LinkedIn ad account for campaign management.

Create Lead Form

Tool to create a new LinkedIn lead generation form for ads.

Get Ad Account

Tool to retrieve a specific LinkedIn Ad Account by ID.

Get Ad Analytics

Tool to retrieve LinkedIn ad analytics and reporting metrics for campaigns, creatives, and accounts.

Get Audience Counts

Get estimated audience size for given targeting criteria on LinkedIn Ads.

Get Campaign Group

Tool to retrieve a specific LinkedIn Ads campaign group by ID.

Get lead form by ID

Tool to retrieve a specific LinkedIn lead form by its ID.

Get organization follower count

Tool to retrieve follower count for a LinkedIn organization.

Get organization access control list

Tool to retrieve organization access control list showing who has admin or poster rights for organizations.

Get organization page statistics

Tool to retrieve page view and click statistics for a LinkedIn organization page.

Get organization follower statistics

Tool to retrieve follower growth statistics for a LinkedIn organization.

Get organization share statistics

Tool to retrieve share and engagement statistics for an organization's content on LinkedIn.

Get Ad Supply Forecasts

Retrieve supply forecasts for LinkedIn ad inventory based on targeting criteria, budget, and bid settings.

Get Targeting Entities

Tool to retrieve targeting entities for LinkedIn Ads campaigns.

Get Targeting Facets

Tool to retrieve available ad targeting facets including industries, locations, seniorities, job functions, skills, and more.

List Conversion Rules

Tool to list all conversion rules for a LinkedIn ad account.

List DMP Segments

Tool to list DMP (Data Management Platform) segments for LinkedIn ad accounts.

List Lead Forms

Tool to list LinkedIn lead forms for an organization or by specific IDs.

List Organizations

Tool to search and list LinkedIn organizations by IDs, vanity name, or parent organization.

List LinkedIn posts

Tool to list LinkedIn posts by author or retrieve multiple posts by IDs.

Lookup organizations

Tool to batch lookup organization details by IDs without requiring admin access.

Register Upload

Tool to register an upload for media assets (images, videos) on LinkedIn.

Search Ad Accounts

Tool to search for LinkedIn ad accounts with filtering by status, type, and test mode.

Search Campaigns

Tool to search and list campaigns in a LinkedIn Ads account with filtering options.

Search LinkedIn Ads Creatives

Tool to search and list LinkedIn Ads creatives with filtering options.

Search Events

Tool to search and list LinkedIn events by organizer with filtering options.

Update lead form

Tool to update an existing LinkedIn lead form.

Update organization access control

Tool to update organization access control for a user on LinkedIn.

FRAMEWORKS

How to build Linkedin Ads MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Linkedin Ads MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Linkedin Ads MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Linkedin Ads MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Linkedin Ads MCP with Claude Cowork

Codex logo

Codex

Use Linkedin Ads MCP with Codex

OpenClaw logo

OpenClaw

Use Linkedin Ads MCP with OpenClaw

Hermes logo

Hermes

Use Linkedin Ads MCP with Hermes

CLI logo

CLI

Use Linkedin Ads MCP with CLI

Google ADK logo

Google ADK

Use Linkedin Ads MCP with Google ADK

LangChain logo

LangChain

Use Linkedin Ads MCP with LangChain

Mastra AI logo

Mastra AI

Use Linkedin Ads MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Linkedin Ads MCP with LlamaIndex

CrewAI logo

CrewAI

Use Linkedin Ads MCP with CrewAI

FAQ

Frequently asked questions

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

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

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