How to integrate Linkedin Ads MCP with LangChain

This guide walks you through connecting Linkedin Ads to LangChain 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 LangChain 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

Oauth2

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 will help you understand how to give your LangChain 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 SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK Vercel AI SDK Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

Get and set up your OpenAI and Composio API keys
Connect your Linkedin Ads project to Composio
Create a Tool Router MCP session for Linkedin Ads
Initialize an MCP client and retrieve Linkedin Ads tools
Build a LangChain agent that can interact with Linkedin Ads
Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

Agent Framework: Build agents that can use tools and make decisions
MCP Integration: Connect to external services through Model Context Protocol adapters
Memory Management: Maintain conversation history across interactions
Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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:

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

Step-by-step Guide

Step by step10 STEPS

Prerequisites

Before starting this tutorial, make sure you have:

Python 3.10 or higher installed on your system
A Composio account with an API key
An OpenAI API key
Basic familiarity with Python and async programming

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.

Install dependencies

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

@composio/langchain provides Composio integration for LangChain
@langchain/mcp-adapters enables MCP client connections
@langchain/core is the core agent framework
dotenv/config loads environment variables

Set up environment variables

bash

COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

COMPOSIO_API_KEY authenticates your requests to Composio's API
COMPOSIO_USER_ID identifies the user for session management
OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();

What's happening:

We're importing LangChain's MCP adapter and Composio SDK
The dotenv/config import loads environment variables from your .env file
This setup prepares the foundation for connecting LangChain with Linkedin Ads functionality through MCP

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

What's happening:

We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
Creating a Composio instance that will manage our connection to Linkedin Ads tools
Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['linkedin_ads']
    }
);

const url = 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 session.mcp.url is the MCP server URL that your agent will use
This approach allows the agent to dynamically load and use Linkedin Ads tools as needed

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "linkedin_ads-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });

What's happening:

We're creating a MultiServerMCPClient that connects to our Linkedin Ads MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Linkedin Ads tools that the agent can use
We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Linkedin Ads related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

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;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });

What's happening:

We initialize an empty conversationHistory list to maintain context across interactions
A readline interface is used to continuously accept user input from the command line
When a user types a message, it's added to the conversation history and sent to the agent
The agent processes the request using the invoke() method with the full conversation history
Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

What's happening:

We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Linkedin Ads and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['linkedin_ads']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "linkedin_ads-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Linkedin Ads related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    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;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Linkedin Ads through Composio's Tool Router.

Key features of this implementation:

Dynamic tool loading through Composio's Tool Router
Conversation history maintenance for context-aware responses
Async Python provides clean, efficient execution of agent workflows

You can extend this further by adding 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.

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

Use Linkedin Ads MCP with OpenAI Agents SDK

Claude Agent SDK

Use Linkedin Ads MCP with Claude Agent SDK

Claude Code

Use Linkedin Ads MCP with Claude Code

Claude Cowork

Use Linkedin Ads MCP with Claude Cowork

Codex

Use Linkedin Ads MCP with Codex

OpenClaw

Use Linkedin Ads MCP with OpenClaw

Hermes

Use Linkedin Ads MCP with Hermes

CLI

Use Linkedin Ads MCP with CLI

Google ADK

Use Linkedin Ads MCP with Google ADK

Vercel AI SDK

Use Linkedin Ads MCP with Vercel AI SDK

Mastra AI

Use Linkedin Ads MCP with Mastra AI

LlamaIndex

Use Linkedin Ads MCP with LlamaIndex

CrewAI

Use Linkedin Ads MCP with CrewAI

MORE TOOLKITS

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Bulk Email Checker

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Bulk Email Checker is an email verification service for checking address validity, mailbox status, domains, and mail-server signals. It helps reduce bounces, spot risky emails, and keep outreach lists cleaner before you send.

Campaign cleaner

Api Key

Campaign cleaner is an email campaign optimization tool that boosts compatibility and deliverability across email clients. It helps marketers get better results by cleaning, enhancing, and ensuring high performance for every campaign.

Deadline funnel

Api Key

Deadline Funnel lets you create personalized deadlines and timers for your marketing campaigns. It helps marketers boost conversions by adding authentic urgency to offers.

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. LangChain 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.

Start with Linkedin Ads.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Linkedin Ads tool your agent needs.Free to start.

Start building

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

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.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Linkedin Ads MCP with LangChain

Connect Linkedin Ads without auth hassles

Introduction

Also integrate Linkedin Ads with

TL;DR

What is LangChain?

What is the Linkedin Ads MCP server, and what's possible with it?

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Initialize Composio client

Create a Tool Router session

Configure the agent with the MCP URL

Set up interactive chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Linkedin Ads MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Adtraction

Bulk Email Checker

Campaign cleaner

Deadline funnel

Frequently asked questions

What are the differences in Tool Router MCP and Linkedin Ads MCP?+

Can I use Tool Router MCP with LangChain?+

Can I manage the permissions and scopes for Linkedin Ads while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Linkedin Ads.It takes 30 seconds.

Teams ship real agents on Composio