# How to integrate Campaign cleaner MCP with Vercel AI SDK v6

```json
{
  "title": "How to integrate Campaign cleaner MCP with Vercel AI SDK v6",
  "toolkit": "Campaign cleaner",
  "toolkit_slug": "campaign_cleaner",
  "framework": "Vercel AI SDK",
  "framework_slug": "ai-sdk",
  "url": "https://composio.dev/toolkits/campaign_cleaner/framework/ai-sdk",
  "markdown_url": "https://composio.dev/toolkits/campaign_cleaner/framework/ai-sdk.md",
  "updated_at": "2026-05-06T08:04:54.675Z"
}
```

## Introduction

This guide walks you through connecting Campaign cleaner to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Campaign cleaner agent that can list all campaigns created this week, download pdf analysis for latest campaign, check status of your july newsletter campaign through natural language commands.
This guide will help you understand how to give your Vercel AI SDK agent real control over a Campaign cleaner account through Composio's Campaign cleaner MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Campaign cleaner with

- [OpenAI Agents SDK](https://composio.dev/toolkits/campaign_cleaner/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/campaign_cleaner/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/campaign_cleaner/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/campaign_cleaner/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/campaign_cleaner/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/campaign_cleaner/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/campaign_cleaner/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/campaign_cleaner/framework/cli)
- [Google ADK](https://composio.dev/toolkits/campaign_cleaner/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/campaign_cleaner/framework/langchain)
- [Mastra AI](https://composio.dev/toolkits/campaign_cleaner/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/campaign_cleaner/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/campaign_cleaner/framework/crew-ai)

## TL;DR

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

The Campaign cleaner MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Campaign cleaner account. It provides structured and secure access to your email campaign data, so your agent can perform actions like listing campaigns, checking campaign status, downloading analysis reports, and deleting campaigns on your behalf.
- Comprehensive campaign listing and retrieval: Easily ask your agent to fetch a complete list of all your saved email campaigns for review, reporting, or management.
- Real-time campaign status monitoring: Let your agent check the processing status of any submitted campaign, so you always know where your campaigns stand.
- Automated PDF analysis downloads: Direct your agent to download detailed PDF analysis reports for any processed campaign, streamlining your optimization workflow.
- Campaign deletion and cleanup: Have your agent safely remove outdated or unnecessary campaigns by confirming and deleting them by ID.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CAMPAIGN_CLEANER_DELETE_CAMPAIGN` | Delete Campaign | Tool to delete a saved campaign by id. use when you need to remove a campaign after confirming its id. |
| `CAMPAIGN_CLEANER_GET_CAMPAIGN_LIST` | Get Campaign List | Tool to list all campaigns in the account. use when you need to retrieve campaign listings for reporting or management. |
| `CAMPAIGN_CLEANER_GET_CAMPAIGN_PDF_ANALYSIS` | Download Campaign PDF Analysis | Tool to download a pdf analysis report for a processed campaign. use after a campaign has been processed. |
| `CAMPAIGN_CLEANER_GET_CAMPAIGN_STATUS` | Get Campaign Status | Tool to check the processing status of a submitted campaign. use after submitting a campaign to monitor its progress. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Campaign cleaner MCP server is an implementation of the Model Context Protocol that connects your AI agent to Campaign cleaner. It provides structured and secure access so your agent can perform Campaign cleaner 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 Campaign cleaner 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 Campaign cleaner-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: ["campaign_cleaner"],
  });

  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 Campaign cleaner 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 campaign_cleaner, 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 Campaign cleaner 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: ["campaign_cleaner"],
  });

  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 campaign_cleaner, 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 Campaign cleaner 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 Campaign cleaner MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/campaign_cleaner/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/campaign_cleaner/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/campaign_cleaner/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/campaign_cleaner/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/campaign_cleaner/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/campaign_cleaner/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/campaign_cleaner/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/campaign_cleaner/framework/cli)
- [Google ADK](https://composio.dev/toolkits/campaign_cleaner/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/campaign_cleaner/framework/langchain)
- [Mastra AI](https://composio.dev/toolkits/campaign_cleaner/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/campaign_cleaner/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/campaign_cleaner/framework/crew-ai)

## Related Toolkits

- [Metaads](https://composio.dev/toolkits/metaads) - Metaads is Meta's official Ads API that lets you manage, analyze, and optimize your Facebook and Instagram ad campaigns. Streamline ad operations and gain deeper insights with robust automation.
- [Adrapid](https://composio.dev/toolkits/adrapid) - Adrapid is a platform for rapid creation of digital marketing visuals using templates. It streamlines design workflows for banners, images, and HTML5 content with automation.
- [Adyntel](https://composio.dev/toolkits/adyntel) - Adyntel is an API that retrieves LinkedIn ads for any company using a domain or LinkedIn Page ID. Easily access competitive ad intelligence to power your marketing workflows.
- [Beaconstac](https://composio.dev/toolkits/beaconstac) - Beaconstac is a platform for creating and managing QR codes and proximity beacons. It helps businesses engage customers and track marketing performance with powerful analytics.
- [Deadline funnel](https://composio.dev/toolkits/deadline_funnel) - Deadline Funnel lets you create personalized deadlines and timers for your marketing campaigns. It helps marketers boost conversions by adding authentic urgency to offers.
- [Google Ads](https://composio.dev/toolkits/googleads) - Google Ads is Google's online advertising platform for creating, managing, and optimizing digital campaigns. It helps businesses reach targeted customers and maximize return on ad spend.
- [Instantly](https://composio.dev/toolkits/instantly) - Instantly is a platform for automating cold email outreach, managing leads, and optimizing deliverability. Get better results from email campaigns with minimal manual effort.
- [Proofly](https://composio.dev/toolkits/proofly) - Proofly is a social proof platform that displays real-time notifications of customer activity on your site. It helps you increase website conversions by building trust and urgency for visitors.
- [Segmetrics](https://composio.dev/toolkits/segmetrics) - Segmetrics is a marketing analytics platform that reveals detailed insights into your customer journeys. It helps businesses optimize marketing strategies with accurate, actionable reporting.
- [Semrush](https://composio.dev/toolkits/semrush) - Semrush is a leading SEO tool suite for keyword research, competitor analysis, and campaign tracking. It empowers marketers to improve search rankings and optimize online visibility.
- [Sendloop](https://composio.dev/toolkits/sendloop) - Sendloop is an all-in-one email marketing platform built for SaaS, e-commerce, and small businesses. It makes it easy to send campaigns, manage lists, and track results—all in one place.
- [Sidetracker](https://composio.dev/toolkits/sidetracker) - Sidetracker is a marketing analytics platform that tracks expenses, sales funnels, and customer journeys. It helps optimize marketing spend and visualize campaign performance from start to finish.
- [Stannp](https://composio.dev/toolkits/stannp) - Stannp is an API-driven direct mail platform for sending postcards and letters programmatically. It lets you automate physical mail delivery—no manual printing or mailing required.
- [Tapfiliate](https://composio.dev/toolkits/tapfiliate) - Tapfiliate is an affiliate and referral tracking platform for businesses. It helps companies efficiently manage, track, and grow their affiliate programs.
- [Tpscheck](https://composio.dev/toolkits/tpscheck) - Tpscheck is a real-time service for verifying UK phone numbers against TPS and CTPS registers. It helps prevent unwanted marketing calls and ensures compliance with UK telemarketing laws.
- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options.
- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Campaign cleaner MCP?

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

### Can I manage the permissions and scopes for Campaign cleaner while using Tool Router?

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)