# How to integrate Kit MCP with Vercel AI SDK v6

```json
{
  "title": "How to integrate Kit MCP with Vercel AI SDK v6",
  "toolkit": "Kit",
  "toolkit_slug": "kit",
  "framework": "Vercel AI SDK",
  "framework_slug": "ai-sdk",
  "url": "https://composio.dev/toolkits/kit/framework/ai-sdk",
  "markdown_url": "https://composio.dev/toolkits/kit/framework/ai-sdk.md",
  "updated_at": "2026-05-06T08:17:38.685Z"
}
```

## Introduction

This guide walks you through connecting Kit to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Kit agent that can add new subscriber to your welcome form, create a custom field for subscriber notes, delete an outdated broadcast by its id through natural language commands.
This guide will help you understand how to give your Vercel AI SDK agent real control over a Kit account through Composio's Kit MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Kit with

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

## TL;DR

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

The Kit MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Kit account. It provides structured and secure access to your subscriber lists, tags, forms, and automations, so your agent can perform actions like managing subscribers, creating tags, updating custom fields, and handling broadcasts on your behalf.
- Subscriber management and automation: Add new subscribers to forms, remove subscribers, or update their details to keep your audience lists accurate and engaged.
- Custom field and tag creation: Automatically create, update, or delete custom fields and tags, making it easy to segment and personalize your communications.
- Webhook and event setup: Set up or remove webhooks so your agent can listen for subscriber or purchase events and trigger automations as needed.
- Broadcast and campaign control: Delete obsolete broadcasts or manage your messaging campaigns directly through your agent for streamlined outreach.
- Account insights and configuration: Retrieve detailed account information, including plan details and primary contact, to keep your integrations and automations running smoothly.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `KIT_ADD_SUBSCRIBER_TO_FORM` | Add Subscriber to Form | Tool to add a subscriber to a specific form by id. use after confirming form and subscriber ids. |
| `KIT_CREATE_CUSTOM_FIELD` | Create Custom Field | Tool to create a new custom field for subscriber data. use when you need to store extra attributes for subscribers. |
| `KIT_CREATE_TAG` | Create Tag | Tool to create a new tag in the account. use when you need a custom label to segment subscribers. use after confirming tag uniqueness to avoid duplicates. example: "create a tag called 'vip' for premium customers." |
| `KIT_CREATE_WEBHOOK` | Create Webhook | Tool to create a new webhook subscription. use when you need subscriber or purchase event notifications. |
| `KIT_DELETE_BROADCAST` | Delete Broadcast | Tool to delete a specific broadcast. use when you need to permanently remove a broadcast by id (after confirming the id). example prompt: "delete broadcast with id 123" |
| `KIT_DELETE_CUSTOM_FIELD` | Delete Custom Field | Tool to delete a specific custom field. use after confirming the custom field id is correct. deletes the field permanently. |
| `KIT_DELETE_SUBSCRIBER` | Delete Subscriber | Tool to delete (unsubscribe) a subscriber by id. use when you need to remove a subscriber from all sequences and forms after confirming the subscriber exists. |
| `KIT_DELETE_TAG` | Delete Tag | Tool to delete a tag by id. use when you need to remove obsolete or incorrect tags after confirming the tag exists. |
| `KIT_DELETE_WEBHOOK` | Delete Webhook | Tool to delete a webhook by id. use when you want to permanently remove a webhook after confirming its id. |
| `KIT_GET_ACCOUNT` | Get Account | Tool to retrieve current account information. use after validating api key to fetch account id, plan type, primary email, and timezone details. |
| `KIT_GET_ACCOUNT_COLORS` | Get Account Colors | Tool to retrieve list of colors associated with the account. use after confirming authentication to fetch account-specific color palette. |
| `KIT_GET_BROADCAST` | Get Broadcast | Tool to retrieve details of a specific broadcast by id. use when you have a valid broadcast id and need its metadata. |
| `KIT_GET_BROADCAST_STATS` | Get Broadcast Stats | Tool to retrieve statistics for a specific broadcast by id. use after a broadcast has been sent to monitor performance. |
| `KIT_GET_CREATOR_PROFILE` | Get Creator Profile | Tool to retrieve the creator profile information for the account. use when you need creator metadata (bio, avatar, social links) before publishing or customizing content. |
| `KIT_GET_EMAIL_STATS` | Get Email Stats | Tool to retrieve email statistics for the account. use after confirming authentication to fetch metrics on emails (sent, opened, clicked) over the last 90 days. |
| `KIT_LIST_BROADCASTS` | List Broadcasts | Tool to retrieve a paginated list of all broadcasts. use when you need to enumerate or review broadcast summaries with cursor-based pagination. |
| `KIT_LIST_CUSTOM_FIELDS` | List Custom Fields | Tool to retrieve a paginated list of custom fields. use after confirming you need to enumerate or inspect all custom fields with cursor-based pagination. |
| `KIT_LIST_FORMS` | List Forms | Tool to list all forms. use when you need to fetch forms with optional filters and pagination. |
| `KIT_LIST_SEGMENTS` | List Segments | Tool to retrieve a paginated list of segments. use when you need to enumerate segments with cursor-based pagination for further processing or display. |
| `KIT_LIST_SEQUENCES` | List Sequences | Tool to retrieve a paginated list of all sequences. use when you need to enumerate sequences with pagination for further processing or display. |
| `KIT_LIST_SUBSCRIBERS` | List Subscribers | Tool to retrieve a list of subscribers. use when you need to fetch subscriber records with optional filtering, sorting, and pagination. |
| `KIT_LIST_SUBSCRIBERS_FOR_FORM` | List Subscribers For Form | Tool to retrieve subscribers for a specific form by id. use when you need to page or filter subscribers of a form. |
| `KIT_LIST_TAGS` | List Tags | Tool to retrieve a list of all tags. use when you need a complete inventory of tags for the kit account. |
| `KIT_LIST_TAG_SUBSCRIBERS` | List Tag Subscribers | Tool to retrieve subscribers for a specific tag. use after confirming the tag id when you need to list subscribers associated with a tag. |
| `KIT_TAG_SUBSCRIBER` | Tag Subscriber | Tool to associate a subscriber with a specific tag by id. use after confirming tag and subscriber ids when tagging a subscriber. |
| `KIT_TAG_SUBSCRIBER_BY_EMAIL` | Tag Subscriber by Email | Tool to associate a subscriber with a tag using an email address. use when you have a tag id and subscriber email ready. use after confirming both resources exist. |
| `KIT_UPDATE_ACCOUNT_COLORS` | Update Account Colors | Tool to update the list of colors for the account. use when customizing your kit account's color palette for broadcasts and templates. |
| `KIT_UPDATE_CUSTOM_FIELD` | Update Custom Field | Tool to update a custom field's label. use after listing or retrieving custom fields and confirming the field id to rename. |
| `KIT_UPDATE_TAG` | Update Tag | Tool to update a tag's name by id. use after retrieving tag id and confirming the new name. |

## Supported Triggers

None listed.

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

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

  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 Kit 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 kit, 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 Kit 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: ["kit"],
  });

  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 kit, 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 Kit 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 Kit MCP Agent with another framework

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

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- [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach.
- [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease.
- [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic.
- [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns.
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- [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place.
- [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES.
- [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.
- [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools.
- [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 Kit MCP?

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

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

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

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