# How to integrate Textit MCP with LangChain

```json
{
  "title": "How to integrate Textit MCP with LangChain",
  "toolkit": "Textit",
  "toolkit_slug": "textit",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/textit/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/textit/framework/langchain.md",
  "updated_at": "2026-05-12T10:28:17.083Z"
}
```

## Introduction

This guide walks you through connecting Textit to LangChain using the Composio tool router. By the end, you'll have a working Textit agent that can create a new campaign for event reminders, list all contact groups for segmentation, retrieve details about a specific campaign through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Textit account through Composio's Textit MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Textit with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Textit project to Composio
- Create a Tool Router MCP session for Textit
- Initialize an MCP client and retrieve Textit tools
- Build a LangChain agent that can interact with Textit
- Set up an interactive chat interface for testing

## What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.
Key features include:
- Agent Framework: Build agents that can use tools and make decisions
- MCP Integration: Connect to external services through Model Context Protocol adapters
- Memory Management: Maintain conversation history across interactions
- Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

## What is the Textit MCP server, and what's possible with it?

The Textit MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Textit account. It provides structured and secure access to your chatbots, contacts, campaigns, and messaging flows, so your agent can create campaigns, manage contact groups, organize labels, retrieve broadcasts, and handle messaging operations on your behalf.
- Automated campaign management: Let your agent create, retrieve, or list messaging campaigns, helping you launch outreach efforts to targeted contact groups without lifting a finger.
- Contact group creation and segmentation: Easily segment your audience by having your agent create or delete contact groups, keeping your communication organized and relevant.
- Custom label organization: Enable your agent to create new message labels, allowing for smarter categorization and easier tracking of important conversations or topics.
- Broadcast and archive retrieval: Effortlessly fetch lists of broadcasts or message archives, so your agent can provide summaries or analyze past messaging performance.
- Contact management: Direct your agent to delete outdated or unnecessary contacts, ensuring your database stays clean and up-to-date automatically.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `TEXTIT_CREATE_CAMPAIGN` | Create Campaign | Tool to create a new campaign in TextIt. Use when you need to start a messaging campaign for a specific contact group. |
| `TEXTIT_CREATE_GROUP` | Create Contact Group | Tool to create a new contact group. Use when segmenting contacts before sending messages. |
| `TEXTIT_CREATE_LABEL` | Create Label | Tool to create a new message label. Use when you need to categorize messages. Example: Create a label 'Important'. Creates a label under your organization using the TextIt Labels API. |
| `TEXTIT_DELETE_CONTACT` | Delete Contact | Tool to delete an existing contact. Use when you have the contact's UUID and need to remove it. |
| `TEXTIT_DELETE_GROUP` | Delete Contact Group | Tool to delete an existing contact group. Use after ensuring the group has no active triggers or campaigns. |
| `TEXTIT_DELETE_LABEL` | Delete Label | Tool to delete a message label by UUID. Use when you need to remove an existing label from your TextIt workspace. |
| `TEXTIT_GET_CAMPAIGN` | Get Campaign | Tool to retrieve details about a specific campaign. Use when you have the campaign's UUID and need its full metadata. |
| `TEXTIT_GET_WORKSPACE` | Get Workspace | Tool to retrieve current workspace details including name, country, languages, and timezone. Use when you need workspace configuration information. |
| `TEXTIT_LIST_ARCHIVES` | List Archives | Tool to retrieve a list of message and run archives. Use when you need to browse or manage existing archives after authenticating. |
| `TEXTIT_LIST_BROADCASTS` | List Broadcasts | Tool to list broadcasts. Use when you need to retrieve broadcasts with optional filters and pagination. |
| `TEXTIT_LIST_CAMPAIGN_EVENTS2` | List Campaign Events 2 | Tool to retrieve campaign events with optional filtering. Use when you need to list scheduled triggers within campaigns, optionally filtering by event UUID or campaign UUID. |
| `TEXTIT_LIST_CAMPAIGNS` | List Campaigns | Tool to list campaigns. Use after authentication to retrieve campaigns, optionally filtering by uuid or date range. |
| `TEXTIT_LIST_CHANNELS` | List Channels | Tool to list channels. Use when you need to retrieve a paginated list of your organization's channels after confirming authentication. |
| `TEXTIT_LIST_CLASSIFIERS` | List Classifiers | Tool to list NLU classifiers configured for your organization. Use when you need to retrieve natural language understanding classifiers (wit.ai, luis, bothub) after confirming authentication. |
| `TEXTIT_LIST_CONTACTS` | List Contacts | Tool to retrieve a list of contacts. Use when you need to fetch contacts with optional filters (UUID, URN, group, or modified date). Use after authenticating your client. |
| `TEXTIT_LIST_FIELDS` | List custom contact fields | Tool to retrieve a list of custom contact fields. Use when you need to view or filter all defined contact fields with pagination and optional search. |
| `TEXTIT_LIST_FLOWS` | List Flows | Tool to retrieve a list of flows for your organization. Use when you need to fetch automated conversation flows with optional filters (UUID, type, archived status, or modified date). |
| `TEXTIT_LIST_FLOW_STARTS` | List Flow Starts | Tool to retrieve a list of manual flow starts. Use when you need to fetch flow start records with optional filters and pagination. |
| `TEXTIT_LIST_GLOBALS` | List Globals | Tool to list global variables. Use when you need to retrieve all workspace-level variables after authenticating. |
| `TEXTIT_LIST_GROUPS2` | List Groups | Tool to list contact groups for your organization. Use when you need to fetch groups with optional filtering by uuid or name. |
| `TEXTIT_LIST_LABELS2` | List Labels 2 | Tool to retrieve a list of message labels for your organization. Use when you need to filter labels by UUID or name. |
| `TEXTIT_LIST_MESSAGES` | List Messages | Tool to retrieve a list of messages. Use when you need to fetch messages with optional filters (UUID, folder, contact, broadcast, or date range). Results are paginated. |
| `TEXTIT_LIST_RESTHOOK_EVENTS` | List Resthook Events | Tool to retrieve recent resthook events for your organization. Use when you need to inspect webhook events that have been triggered, optionally filtered by resthook slug. Events are returned in reverse chronological order. |
| `TEXTIT_LIST_RESTHOOKS` | List Resthooks | Tool to list configured resthooks (webhooks). Use when you need to retrieve the resthooks configured in your TextIt account. |
| `TEXTIT_LIST_RESTHOOK_SUBSCRIBERS` | List Resthook Subscribers | Tool to list webhook subscribers for your organization's resthooks. Use when you need to retrieve the target URLs that receive webhook events for specific resthooks. |
| `TEXTIT_LIST_RUNS` | List Runs | Tool to retrieve a list of flow runs. Use when you need to filter or browse run history by flow, contact, or status. |
| `TEXTIT_LIST_TICKETS` | List Tickets | Tool to retrieve support tickets for your organization. Use when you need to fetch tickets with optional filters (UUID, contact, topic, or assignee). Returns paginated ticket data. |
| `TEXTIT_LIST_TOPICS2` | List Topics V2 | Tool to list topics in the workspace for categorizing tickets. Use when you need to retrieve topics, optionally filtered by UUID. |
| `TEXTIT_LIST_USERS` | List Users | Tool to retrieve a list of user logins in your workspace with their roles and teams. Use when you need to fetch users with optional UUID filter. Results are ordered by newest created first. |
| `TEXTIT_SEND_BROADCAST` | Send Broadcast | Tool to send a new broadcast message. Use after composing message translations and selecting recipients (urns, contacts, or groups). |
| `TEXTIT_UPDATE_CONTACT` | Update Contact | Tool to update an existing contact. Use after identifying the contact's UUID or URN and preparing details. |

## Supported Triggers

None listed.

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

The Textit MCP server is an implementation of the Model Context Protocol that connects your AI agent to Textit. It provides structured and secure access so your agent can perform Textit 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

No description provided.

### 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 dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio's API
- COMPOSIO_USER_ID identifies the user for session management
- OPENAI_API_KEY enables access to OpenAI's language models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

What's happening:
- We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
- Creating a Composio instance that will manage our connection to Textit tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Textit tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned session.mcp.url is the MCP server URL that your agent will use
- This approach allows the agent to dynamically load and use Textit tools as needed
```python
# Create Tool Router session for Textit
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['textit']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['textit']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "textit-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "textit-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Textit related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Textit related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

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;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['textit']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "textit-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Textit related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['textit']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "textit-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Textit related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    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;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Conclusion

You've successfully built a LangChain agent that can interact with Textit through Composio's Tool Router.
Key features of this implementation:
- Dynamic tool loading through Composio's Tool Router
- Conversation history maintenance for context-aware responses
- Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## How to build Textit MCP Agent with another framework

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

## Related Toolkits

- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Slack](https://composio.dev/toolkits/slack) - Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.
- [Gong](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.
- [Microsoft teams](https://composio.dev/toolkits/microsoft_teams) - Microsoft Teams is a collaboration platform that combines chat, meetings, and file sharing within Microsoft 365. It keeps distributed teams connected and productive through seamless virtual communication.
- [Slackbot](https://composio.dev/toolkits/slackbot) - Slackbot is a conversational automation tool for Slack that handles reminders, notifications, and automated responses. It boosts team productivity by streamlining onboarding, answering FAQs, and managing timely alerts—all right inside Slack.
- [2chat](https://composio.dev/toolkits/_2chat) - 2chat is an API platform for WhatsApp and multichannel text messaging. It streamlines chat automation, group management, and real-time messaging for developers.
- [Agent mail](https://composio.dev/toolkits/agent_mail) - Agent mail provides AI agents with dedicated email inboxes for sending, receiving, and managing emails. It empowers agents to communicate autonomously with people, services, and other agents—no human intervention needed.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Chatwork](https://composio.dev/toolkits/chatwork) - Chatwork is a team communication platform with group chats, file sharing, and task management. It helps businesses boost collaboration and streamline productivity.
- [Clickmeeting](https://composio.dev/toolkits/clickmeeting) - ClickMeeting is a cloud-based platform for running online meetings and webinars. It helps businesses and individuals host, manage, and engage virtual audiences with ease.
- [Confluence](https://composio.dev/toolkits/confluence) - Confluence is Atlassian's team collaboration and knowledge management platform. It helps your team organize, share, and update documents and project content in one secure workspace.
- [Dailybot](https://composio.dev/toolkits/dailybot) - DailyBot streamlines team collaboration with chat-based standups, reminders, and polls. It keeps work flowing smoothly in your favorite messaging platforms.
- [Dialmycalls](https://composio.dev/toolkits/dialmycalls) - Dialmycalls is a mass notification service for sending voice and text messages to contacts. It helps teams and organizations quickly broadcast urgent alerts and updates.
- [Dialpad](https://composio.dev/toolkits/dialpad) - Dialpad is a cloud-based business phone and contact center system for teams. It unifies voice, video, messaging, and meetings across your devices.
- [Discord](https://composio.dev/toolkits/discord) - Discord is a real-time messaging and VoIP platform for communities and teams. It lets users chat, share media, and collaborate across public and private channels.
- [Discordbot](https://composio.dev/toolkits/discordbot) - Discordbot is an automation tool for Discord servers that handles moderation, messaging, and user engagement. It helps communities run smoothly by automating routine and complex tasks.
- [Echtpost](https://composio.dev/toolkits/echtpost) - Echtpost is a secure digital communication platform for encrypted document and message exchange. It ensures confidential data stays private and protected during transmission.
- [Egnyte](https://composio.dev/toolkits/egnyte) - Egnyte is a cloud-based platform for secure file sharing, storage, and governance. It helps teams collaborate efficiently while maintaining data compliance and security.
- [Google Meet](https://composio.dev/toolkits/googlemeet) - Google Meet is a secure video conferencing platform for virtual meetings, chat, and screen sharing. It helps teams connect, collaborate, and communicate seamlessly from anywhere.

## Frequently Asked Questions

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

With a standalone Textit MCP server, the agents and LLMs can only access a fixed set of Textit tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Textit and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain 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 Textit tools.

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

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

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