# How to integrate Dripcel MCP with Vercel AI SDK v6

```json
{
  "title": "How to integrate Dripcel MCP with Vercel AI SDK v6",
  "toolkit": "Dripcel",
  "toolkit_slug": "dripcel",
  "framework": "Vercel AI SDK",
  "framework_slug": "ai-sdk",
  "url": "https://composio.dev/toolkits/dripcel/framework/ai-sdk",
  "markdown_url": "https://composio.dev/toolkits/dripcel/framework/ai-sdk.md",
  "updated_at": "2026-05-12T10:09:47.790Z"
}
```

## Introduction

This guide walks you through connecting Dripcel to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Dripcel agent that can send sms promotion to new signups, check current dripcel credit balance, list replies to last week's campaigns through natural language commands.
This guide will help you understand how to give your Vercel AI SDK agent real control over a Dripcel account through Composio's Dripcel MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Dripcel with

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

## TL;DR

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

The Dripcel MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dripcel account. It provides structured and secure access to your SMS marketing campaigns, contacts, and analytics, so your agent can perform actions like sending messages, managing contacts, retrieving campaign results, and optimizing compliance checks on your behalf.
- Automated SMS sending and scheduling: Easily instruct your agent to send targeted SMS messages to customers or schedule campaign deliveries for maximum impact.
- Contact and tag management: Have your agent add tags to contacts, create new contacts on the fly, or delete outdated ones to keep your audience list clean and organized.
- Campaign and delivery analytics: Let your agent fetch real-time campaign lists, delivery statuses, and sales data to keep you informed and support data-driven decisions.
- Reply and compliance monitoring: Direct your agent to search for message replies using flexible filters or check your contact list against compliance rules before launching campaigns.
- Credit balance and resources tracking: Ask your agent to check your current credit balance before sending messages or running large campaigns, ensuring uninterrupted operations.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DRIPCEL_CREATE_CONTACTS` | Create Contacts in Bulk | Tool to upload a list of new contacts to Dripcel in bulk. Only creates new contacts (does not update existing ones). Use when you need to add multiple contacts to your Dripcel account at once. Maximum 100,000 contacts per request. |
| `DRIPCEL_DELETE_CONTACT` | Delete Contact | Tool to delete a contact by their cell number. Use when you need to remove a contact from Dripcel after confirming the MSISDN. |
| `DRIPCEL_DELETE_TAG` | Delete Tag | Tool to delete a tag by its ID. Use when you need to remove a tag from Dripcel. Warning: This will also remove the tag from all contacts and campaigns that have it. |
| `DRIPCEL_GET_BALANCE` | Get current credit balance | Retrieves the current credit balance for your Dripcel organization account. This action requires no input parameters and returns the available credit balance as a numeric value. Use this to check your account balance before performing credit-consuming operations like sending SMS messages. The balance is returned in your account's default currency (not explicitly specified in the response). |
| `DRIPCEL_DRIPCEL_GET_CAMPAIGNS` | Get Dripcel Campaigns | Retrieves a list of campaigns from Dripcel. Supports optional pagination (page, pageSize) and filtering by campaign status. Returns campaign details including ID, name, status, and timestamps. |
| `DRIPCEL_GET_CONTACT` | Get contact by cell number | Tool to retrieve a single contact by their cell number (MSISDN). Use when you need to view details of a specific contact including their name, email, tags, and other metadata. |
| `DRIPCEL_GET_DELIVERIES` | Get Deliveries | Tool to retrieve SMS/email delivery records from Dripcel. Returns a list of message deliveries filtered by recipient phone number (cell) or send operation ID (customerId). Useful for tracking message delivery status, checking delivery history for a specific contact, or auditing a particular send operation. |
| `DRIPCEL_GET_EMAIL_TEMPLATES` | Get email templates | Retrieves all email templates from your Dripcel account. Returns a list of templates with their IDs, names, subjects, and content. Use this action when you need to: - View all available email templates in your account - Get template IDs for use in email sending operations - Check template content before selecting one for a campaign - List templates to verify template creation or updates Note: According to API documentation, this endpoint returns all templates without documented support for pagination or filtering. |
| `DRIPCEL_GET_SALES` | Get sales | Tool to retrieve a list of all sales. Use when you need comprehensive sales data for reporting or analytics. |
| `DRIPCEL_LIST_TAGS` | List all tags | Tool to retrieve all tags in your Dripcel organization. Use when you need to view available tags, get tag IDs for adding to contacts, or verify tag existence before operations. |
| `DRIPCEL_OPT_OUT_CONTACT` | Opt out contact from campaigns | Tool to opt out a contact from multiple campaigns at once. Use when you need to remove a contact from campaign messaging. More robust than single campaign opt-out, allowing batch operations or opting out from all campaigns at once. |
| `DRIPCEL_POST_COMPLIANCE_SEND` | Check SMS Compliance | Check if phone numbers are allowed to receive SMS messages based on opt-out status and campaign targeting rules. Returns whether each number can be sent to, helping ensure compliance before sending messages. Costs 0.14 credits per phone number checked. |
| `DRIPCEL_POST_REPLIES_SEARCH` | Search replies based on filters | Search for SMS/message replies with flexible filtering by ID, campaign, phone number, reply type, message content, or date range. Returns matching replies with metadata. All filters are optional and can be combined for precise queries. |
| `DRIPCEL_PUT_CONTACT_TAG_ADD` | Add tags to a contact | Add one or more tags to a contact identified by phone number. Use this tool to organize contacts by assigning tags for segmentation and targeting. Tags must exist in the system before being added - use GET /tags to retrieve valid tag IDs. Provide either tag_ids (recommended) or tag names. Set create_missing_contact=true to automatically create the contact if they don't exist in your Dripcel account. Response includes matchedCount (contacts found) and modifiedCount (contacts updated). |
| `DRIPCEL_SEARCH_SEND_LOGS` | Search send logs | Search for SMS send logs with flexible filtering by ID, phone number, campaign, delivery, message content (regex), or date range. Supports MongoDB-style queries with projection and pagination. All filters are optional and can be combined. |
| `DRIPCEL_SEND_BULK_EMAIL` | Send Bulk Email | Tool to send bulk emails to multiple recipients using a template. Use when you need to send the same email content to many contacts at once. |
| `DRIPCEL_SEND_SMS` | Send SMS | Tool to send a single SMS to a contact. Use when you need to deliver a targeted message immediately or schedule it for later. |
| `DRIPCEL_UPSERT_CONTACTS` | Upsert Contacts | Tool to upload contacts in bulk, creating new contacts or updating existing ones. Limit: 20,000 contacts per request. Use when you need to import or sync a list of contacts to Dripcel. Invalid contacts will be reported but won't block the operation. |

## Supported Triggers

None listed.

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

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

  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 Dripcel 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 dripcel, 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 Dripcel 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: ["dripcel"],
  });

  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 dripcel, 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 Dripcel 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 Dripcel MCP Agent with another framework

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

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- [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere.
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- [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools.
- [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes.
- [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management.
- [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals.
- [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams.
- [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience.
- [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs.
- [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Dripcel MCP?

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

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

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

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