# How to integrate Gatherup MCP with Vercel AI SDK v6

```json
{
  "title": "How to integrate Gatherup MCP with Vercel AI SDK v6",
  "toolkit": "Gatherup",
  "toolkit_slug": "gatherup",
  "framework": "Vercel AI SDK",
  "framework_slug": "ai-sdk",
  "url": "https://composio.dev/toolkits/gatherup/framework/ai-sdk",
  "markdown_url": "https://composio.dev/toolkits/gatherup/framework/ai-sdk.md",
  "updated_at": "2026-05-12T10:12:35.596Z"
}
```

## Introduction

This guide walks you through connecting Gatherup to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Gatherup agent that can send feedback request to recent customer, retrieve details for a specific business, search for business using custom field through natural language commands.
This guide will help you understand how to give your Vercel AI SDK agent real control over a Gatherup account through Composio's Gatherup MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Gatherup with

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

## TL;DR

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

The Gatherup MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Gatherup account. It provides structured and secure access to your customer feedback and business review data, so your agent can perform actions like fetching customer and business details, sending feedback requests, searching businesses, and managing business profiles on your behalf.
- Send automated feedback requests: Have your agent send personalized feedback invitations to customers right after an interaction, streamlining your review gathering process.
- Retrieve business and customer details: Instantly pull up specific business locations or customer profiles using IDs for quick reference and reporting.
- Search business locations efficiently: Let your agent find businesses by custom fields or extra attributes, making it easy to manage multiple locations or franchises.
- Manage business records securely: Direct your agent to delete business locations or update details after validating credentials and signatures.
- Access and filter business types: Enable your agent to fetch available business type identifiers for accurate categorization and reporting.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GATHERUP_DELETE_BUSINESS` | Delete GatherUp Business | Permanently deletes a business location from GatherUp. This is a destructive operation that cannot be undone. **When to use**: Remove business locations that are no longer needed or were created in error. **Important**: Verify the businessId before deletion. Check errorCode in response: 0=success, non-zero=error. |
| `GATHERUP_FIND_AGENCY_CLIENT_ID` | Find GatherUp Agency Client ID | Find the client ID for a specific business in GatherUp agency accounts. This tool retrieves the numeric client identifier associated with a business location. Use this when you need to look up the client ID for agency-level operations or business management. |
| `GATHERUP_GET_BUSINESS` | Get GatherUp Business | Retrieve detailed information about a specific GatherUp business location. Returns comprehensive business data including: name, contact details (phone, address), timezone, business type, subscription package, communication settings, engagement metrics (NPS score, feedback counts), and marketing assets (logos, banners, feedback URLs). Prerequisites: - Use GATHERUP_SEARCH_BUSINESS if you need to find a businessId by customField/extraField |
| `GATHERUP_GET_BUSINESS_TYPES` | Get GatherUp Business Types | Retrieves the list of available business categories from GatherUp (e.g., Restaurant, Hotel, Dental Office). Use this to: - Get valid business type IDs for creating new businesses - Discover available business categories in GatherUp - Filter business types by search term (optional) |
| `GATHERUP_GET_CUSTOMER` | Get GatherUp Customer | Retrieves detailed information about a specific customer from GatherUp by their customer ID. Use this action to get customer details including name, email, phone, rating, feedback status, and other customer-related information. Common use cases: - Retrieve customer contact information before sending feedback requests - Check customer's current rating and feedback status - Verify customer subscription status (unsubscribed flag) - Get customer creation date and associated business details Error codes: 0=success, 2=invalid clientId, 3=server error, 44=customer not found Endpoint: POST https://app.gatherup.com/api/customer/get |
| `GATHERUP_GET_WIDGET_HTML` | Get Widget HTML | Retrieve pre-formatted widget or badge HTML code with schema.org structure and SEO-friendly content. Returns ready-to-embed HTML code that displays customer reviews or badges on your website. The HTML includes structured data markup for better search engine visibility. Prerequisites: - Use GATHERUP_SEARCH_BUSINESS if you need to find a businessId |
| `GATHERUP_SEARCH_BUSINESS` | Search GatherUp Business by Custom Identifier | Search for a GatherUp business location by custom identifier and retrieve its business ID. This tool locates business locations using user-defined identifiers (customField or extraField) that you've assigned in GatherUp. Returns the businessId on success (errorCode=0), or an error code with message on failure. Common error codes: 2=Invalid clientId, 25=Business not found, 26=Invalid search type Endpoint: POST /api/business/search |
| `GATHERUP_SEND_CUSTOMER_FEEDBACK` | Send GatherUp Customer Feedback | Send a feedback request to a customer to collect their rating and review. Use this when you want to automatically request feedback after a customer interaction or transaction. Ensure the customer exists in your GatherUp account and hasn't unsubscribed from feedback requests. |
| `GATHERUP_SET_USER_PASSWORD` | Set GatherUp User Password | Sets a new password for an existing user in GatherUp. Use this action to update user credentials securely. **Prerequisites**: - Valid userId (user must exist in your GatherUp account) - Password must meet security requirements: minimum 12 characters, at least one uppercase letter and one number **When to use**: Update user passwords for security purposes or user account management. Check errorCode in response: 0=success, non-zero=error. See errorMessage for details. |

## Supported Triggers

None listed.

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

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

  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 Gatherup 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 gatherup, 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 Gatherup 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: ["gatherup"],
  });

  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 gatherup, 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 Gatherup 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 Gatherup MCP Agent with another framework

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

## Related Toolkits

- [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools.
- [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations.
- [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates.
- [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates.
- [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. It helps businesses automate support and streamline interactions through natural, voice-powered conversations.
- [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code.
- [Botstar](https://composio.dev/toolkits/botstar) - BotStar is a comprehensive chatbot platform for designing, developing, and training chatbots visually on Messenger and websites. It helps businesses automate conversations and customer interactions without coding.
- [Callerapi](https://composio.dev/toolkits/callerapi) - CallerAPI is a white-label caller identification platform for branded caller ID and fraud prevention. It helps businesses boost customer trust while stopping spam, fraud, and robocalls.
- [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources.
- [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates.
- [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality.
- [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster.
- [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment.
- [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support.
- [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach.
- [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses.

## Frequently Asked Questions

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

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

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

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

---
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