# How to integrate Acculynx MCP with Vercel AI SDK v6

```json
{
  "title": "How to integrate Acculynx MCP with Vercel AI SDK v6",
  "toolkit": "Acculynx",
  "toolkit_slug": "acculynx",
  "framework": "Vercel AI SDK",
  "framework_slug": "ai-sdk",
  "url": "https://composio.dev/toolkits/acculynx/framework/ai-sdk",
  "markdown_url": "https://composio.dev/toolkits/acculynx/framework/ai-sdk.md",
  "updated_at": "2026-05-06T07:59:10.340Z"
}
```

## Introduction

This guide walks you through connecting Acculynx to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Acculynx agent that can add new roofing lead from web form, schedule site visit for job tomorrow, list all appointments for job 12345 through natural language commands.
This guide will help you understand how to give your Vercel AI SDK agent real control over a Acculynx account through Composio's Acculynx MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Acculynx with

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

## TL;DR

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

The Acculynx MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Acculynx account. It provides structured and secure access to your construction project data, so your agent can create jobs, manage contacts, schedule appointments, and organize calendars on your behalf.
- Automated job creation and management: Instantly create new jobs in your Acculynx system, specifying contacts, addresses, categories, and more to streamline project setup.
- Contact and lead management: Add new contacts or leads with detailed information, helping you keep your pipeline up to date and organized without manual data entry.
- Appointment scheduling and tracking: Schedule initial job appointments or retrieve summaries of all job-related events, making it easy to keep teams and clients in sync.
- Company representative assignment: Assign representatives to specific jobs to clarify project responsibilities and maintain accurate records of team involvement.
- Calendar and contact type retrieval: Fetch lists of company calendars or contact types, supporting smarter scheduling, filtering, and contact management across your organization.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ACCULYNX_ADD_JOB_APPOINTMENT` | Add job appointment | This endpoint allows users to schedule the initial appointment for a specific job in the acculynx system. it is used to set up the first meeting or site visit for a construction or roofing project. the endpoint requires the job id, start date and time, and end date and time for the appointment. this is crucial for initiating the project workflow and ensuring that all parties involved are aware of the scheduled time for the first interaction. the appointment details are set in the context of the company's timezone unless otherwise specified. use this endpoint when a new job has been created and the first appointment needs to be scheduled with the client or at the job site. |
| `ACCULYNX_CREATE_A_CONTACT` | Create a contact | Creates a new contact in the acculynx system with detailed information for use in roofing and construction project management. this endpoint allows for the addition of comprehensive contact details including personal information, company affiliation, communication preferences, and address information. it's particularly useful for adding new customers, leads, vendors, or any other type of contact relevant to construction projects. the endpoint provides flexibility in the amount of information that can be added, with only the contact type being required. use this when you need to add a new contact to your acculynx database or update your system with new lead information. note that while many fields are optional, providing as much information as possible will enhance the usefulness of the contact record for future project management and communication purposes. |
| `ACCULYNX_CREATE_A_JOB` | Create a job | Creates a new job in the acculynx system with the provided details. this endpoint allows you to initialize a job with essential information such as the associated contact, location, job category, work type, priority, and trade types. it's particularly useful for setting up new projects or tasks within the acculynx platform for the roofing and construction industries. the endpoint requires at minimum a contact id and location address, with several optional fields to further customize the job entry. use this when you need to programmatically create new jobs in acculynx, such as when integrating with other systems or automating job creation processes. |
| `ACCULYNX_CREATE_A_LEAD` | Create a lead | This endpoint creates a new lead in the acculynx system, specifically for residential roofing projects. it should be used when a new potential customer expresses interest in roofing services or when importing lead data from external sources. the endpoint captures essential contact information to initiate the lead management process. while it creates the lead, it does not assign priorities or sales representatives; these actions would need to be performed separately. the endpoint is designed for simplicity and quick lead entry, focusing on the most crucial identifying information. |
| `ACCULYNX_JOB_APPOINTMENT_SUMMARY` | Job appointment summary | Retrieves a list of appointments from the calendar associated with a specific job in acculynx. this endpoint is used to fetch scheduled events, such as site visits, inspections, or project milestones, for a particular roofing or construction job. it provides valuable information for project management and scheduling purposes. the endpoint should be used when you need to view or manage the timeline of events for a specific job. it will not provide general calendar information or appointments unrelated to the specified job id. the response likely includes details such as appointment dates, times, descriptions, and associated team members, though the exact structure is not specified in the given schema. |
| `ACCULYNX_LIST_OF_CALENDARS_FOR_THE_LOCATION` | List of calendars for the location | Retrieves a list of calendars associated with the authenticated user or organization in acculynx. this endpoint provides access to the calendar data, which is crucial for scheduling and organizing tasks in the roofing and construction project management context. it should be used when you need to obtain an overview of all available calendars or to gather calendar ids for use in other api operations. the endpoint returns basic information about each calendar, likely including identifiers, names, and possibly associated metadata. it does not modify any calendar data and is intended for read-only operations. keep in mind that the response may be paginated for large datasets, and additional parameters might be available for filtering or sorting the results, although they are not specified in the current schema. |
| `ACCULYNX_LIST_OF_CONTACT_TYPES_RELATED_TO_THE_COMPANY` | List of contact types related to the company | Retrieves a list of all available contact types in the acculynx system. this endpoint is used to fetch the predefined categories or classifications for contacts, such as residential, repair, property management, and other job categories. it's essential for organizing and filtering contact information within the acculynx platform. the endpoint should be used when setting up new contacts, updating existing ones, or when needing to populate dropdown menus or filter options in the user interface. it does not create, modify, or delete contact types; it only provides the current list of available options. the response will likely include unique identifiers and names for each contact type, allowing for easy integration with other parts of the acculynx api or external systems. |
| `ACCULYNX_UPDATE_COMPANY_REPRESENTATIVE` | Update company representative | This endpoint allows you to add a company representative to a specific job within the acculynx system. it is used when you need to associate a representative with a particular project or task. the endpoint requires the job's unique identifier and the representative's id to establish the connection. this operation is useful for assigning personnel to projects, tracking responsibilities, and maintaining accurate job records. it's important to note that this endpoint only adds the association and doesn't create new representative or job entries. |

## Supported Triggers

None listed.

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

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

  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 Acculynx 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 acculynx, 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 Acculynx 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: ["acculynx"],
  });

  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 acculynx, 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 Acculynx 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 Acculynx MCP Agent with another framework

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

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- [Capsule crm](https://composio.dev/toolkits/capsule_crm) - Capsule CRM is a user-friendly CRM platform for managing contacts and sales pipelines. It helps businesses organize relationships and streamline their sales process efficiently.
- [Centralstationcrm](https://composio.dev/toolkits/centralstationcrm) - CentralStationCRM is an easy-to-use CRM software focused on collaboration and long-term customer relationships. It helps teams manage contacts, deals, and communications all in one place.
- [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.
- [Close](https://composio.dev/toolkits/close) - Close is a CRM platform built for sales teams, combining calling, email automation, and predictive dialers. It streamlines sales workflows and boosts productivity with all-in-one communication tools.
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- [Dynamics365](https://composio.dev/toolkits/dynamics365) - Dynamics 365 is Microsoft's platform combining CRM, ERP, and productivity apps. It streamlines sales, marketing, service, and operations in one place.
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- [Fireberry](https://composio.dev/toolkits/fireberry) - Fireberry is a CRM platform that streamlines customer and sales management. It helps businesses organize contacts, automate sales, and integrate with other business tools.
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## Frequently Asked Questions

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

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

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

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

---
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