# How to integrate Heyreach MCP with Vercel AI SDK v6

```json
{
  "title": "How to integrate Heyreach MCP with Vercel AI SDK v6",
  "toolkit": "Heyreach",
  "toolkit_slug": "heyreach",
  "framework": "Vercel AI SDK",
  "framework_slug": "ai-sdk",
  "url": "https://composio.dev/toolkits/heyreach/framework/ai-sdk",
  "markdown_url": "https://composio.dev/toolkits/heyreach/framework/ai-sdk.md",
  "updated_at": "2026-05-12T10:14:55.066Z"
}
```

## Introduction

This guide walks you through connecting Heyreach to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Heyreach agent that can list all active outreach campaigns, get all leads from your main list, fetch linkedin accounts connected to heyreach through natural language commands.
This guide will help you understand how to give your Vercel AI SDK agent real control over a Heyreach account through Composio's Heyreach MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Heyreach with

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

## TL;DR

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

The Heyreach MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Heyreach account. It provides structured and secure access to your outreach platform, so your agent can perform actions like managing campaigns, handling leads, creating lists, and automating webhooks on your behalf.
- Campaign management and reporting: Retrieve and review all your active, scheduled, or past campaigns, enabling your agent to keep your outreach strategy organized and up to date.
- Lead and list operations: Fetch all leads from any list, create new empty lists, and get a full overview of your audience segments—making bulk actions and lead tracking a breeze.
- Webhook automation: Set up or delete webhooks programmatically, so your agent can automate notifications and integrate Heyreach data with other tools without manual effort.
- LinkedIn account integration: Access and manage all connected LinkedIn accounts, streamlining multi-channel outreach and coordination directly from your AI assistant.
- Company and data retrieval: Pull companies from specific lists and get detailed records, helping your agent power richer, more personalized engagement workflows.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `HEYREACH_ADD_LEADS_TO_LIST_V2` | Add Leads To List V2 | Tool to add leads to a lead list in HeyReach for LinkedIn campaigns. Accepts up to 100 leads per request and returns counts of added, updated, and failed leads. |
| `HEYREACH_CHECK_API_KEY` | Check API Key | Tool to check if the API key is valid. Use before making other API calls to confirm authentication. |
| `HEYREACH_CREATE_EMPTY_LIST` | Create Empty List | Tool to create an empty list. Use after deciding on the list name and type. |
| `HEYREACH_CREATE_TAGS` | Create Tags | Tool to create one or multiple tags for your workspace. Use when you need to organize leads with custom labels. |
| `HEYREACH_CREATE_WEBHOOK` | Create Webhook | Tool to create a new webhook. Use when you need programmatic callbacks for HeyReach events after confirming a valid API key. |
| `HEYREACH_DELETE_WEBHOOK` | Delete Webhook | Tool to delete an existing webhook. Use when you need to remove callbacks for outdated or unwanted webhooks. |
| `HEYREACH_GET_ALL_CAMPAIGNS` | Get All Campaigns | Tool to retrieve all campaigns. Use when you need a paginated list of campaigns for management or reporting. |
| `HEYREACH_GET_ALL_LEADS` | Get All Leads | Tool to retrieve all leads in a HeyReach list. Use when you need paginated collection of leads after confirming a valid API key. |
| `HEYREACH_GET_ALL_LINKEDIN_ACCOUNTS` | Get All LinkedIn Accounts | Tool to retrieve all LinkedIn accounts. Use when you need a paginated list of LinkedIn accounts after confirming a valid API key. |
| `HEYREACH_GET_ALL_LISTS` | Get All Lists | Tool to retrieve all lists. Use when you need a paginated list of lists after confirming a valid API key. |
| `HEYREACH_GET_ALL_WEBHOOKS` | Get All Webhooks | Tool to retrieve all webhooks. Use when you need a paginated collection of webhooks after confirming a valid API key. |
| `HEYREACH_GET_COMPANIES_FROM_LIST` | Get Companies From List | Tool to get companies from a company list. Use when you need a paginated list of companies after specifying a list ID. |
| `HEYREACH_GET_CONVERSATIONS_V2` | Get Conversations V2 | Tool to retrieve paginated LinkedIn conversations with advanced filters. Use when you need to fetch inbox conversations filtered by lead or profile details. |
| `HEYREACH_GET_LEAD` | Get Lead | Tool to retrieve detailed information for a lead by profile URL. Use after obtaining the exact LinkedIn profile URL to fetch full lead details. |
| `HEYREACH_GET_LISTS_FOR_LEAD` | Get Lists For Lead | Tool to retrieve all lists that contain a specific lead by profile URL. Use when you need to find which lists a lead belongs to. |
| `HEYREACH_GET_MY_NETWORK_FOR_SENDER` | Get My Network for Sender | Tool to get the LinkedIn network for a specified sender account. Use when you need to retrieve paginated connections for a sender. |
| `HEYREACH_GET_OVERALL_STATS` | Get Overall Stats | Tool to get overall statistics for LinkedIn accounts and campaigns. Use when you need performance metrics including connection requests, messages, replies, and engagement rates for specified date ranges. |
| `HEYREACH_GET_WEBHOOK_BY_ID` | Get Webhook By ID | Tool to retrieve a webhook by its ID. Use when you need detailed configuration of a specific webhook after listing or creating it. |
| `HEYREACH_UPDATE_WEBHOOK` | Update Webhook | Tool to update an existing webhook’s configuration. Use when you need to modify a webhook's name, URL, event type, campaigns, or activation status after confirming the webhookId. |

## Supported Triggers

None listed.

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

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

  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 Heyreach 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 heyreach, 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 Heyreach 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: ["heyreach"],
  });

  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 heyreach, 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 Heyreach 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 Heyreach MCP Agent with another framework

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

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

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

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

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