# How to integrate Reply io MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Reply io MCP with OpenAI Agents SDK",
  "toolkit": "Reply io",
  "toolkit_slug": "reply_io",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/reply_io/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/reply_io/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:23:56.407Z"
}
```

## Introduction

This guide walks you through connecting Reply io to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Reply io agent that can list all active campaigns this week, show contacts added to sales lists, delete a campaign by campaign id through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Reply io account through Composio's Reply io MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Reply io with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Reply io
- Configure an AI agent that can use Reply io as a tool
- Run a live chat session where you can ask the agent to perform Reply io operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

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

The Reply io MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Reply io account. It provides structured and secure access to your sales engagement platform, so your agent can manage campaigns, handle contacts, organize sequences, and automate routine sales operations on your behalf.
- Campaign and sequence management: Effortlessly list, browse, and delete campaigns or sequences to keep your outreach organized and up to date.
- Contact and list organization: Let your agent fetch, review, and organize your Reply io contacts and contact lists for targeted sales actions.
- Email account administration: Retrieve all connected email accounts or remove outdated ones, making sure your sales tools stay streamlined.
- User and access control: Easily remove users or generate unique identifiers for tasks, maintaining security and clarity in your team’s workflow.
- Automated data retrieval: Quickly pull up paginated lists of campaigns, sequences, email accounts, or contact lists to inform your sales strategies and next steps.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `REPLY_IO_ADD_CONTACT_TO_SEQUENCE` | Add Contact to Sequence | Move an existing contact to a sequence in Reply.io. Use this action to enroll contacts in email sequences for automated outreach campaigns. This action allows you to specify where in the sequence to start, whether to remove the contact from their current sequence, and when to begin processing. |
| `REPLY_IO_ARCHIVE_SEQUENCE` | Archive Sequence | Tool to archive a sequence. Use when you need to archive an existing sequence without permanently deleting it. |
| `REPLY_IO_CLEAR_CONTACT_STATUS` | Clear Contact Status | Tool to clear statuses from contacts. Use when you need to remove specific or all clearable statuses from contacts. |
| `REPLY_IO_CONNECT_EXCHANGE_ACCOUNT` | Connect Exchange Account via OAuth | Tool to initiate OAuth connection for an Exchange email account. Use when you need to connect an Exchange account to Reply.io via OAuth flow. Returns the Microsoft OAuth consent page URL where the user should be redirected. |
| `REPLY_IO_CONNECT_GMAIL_ACCOUNT` | Connect Gmail Account | Tool to initiate Gmail account connection via OAuth. Returns the OAuth authorization URL where the user should be redirected to grant permissions. |
| `REPLY_IO_CREATE_CONTACT` | Create Contact | Tool to create a new contact in Reply.io. Use when adding contacts to your outreach database. |
| `REPLY_IO_CREATE_SEQUENCE_STEP` | Create Sequence Step | Tool to add a new step to an existing sequence. Use when you need to build or modify sequence workflows with Email, Call, Task, SMS, WhatsApp, LinkedIn, Condition, or Zapier steps. |
| `REPLY_IO_DELETE_CONTACT` | Delete Contact | Tool to delete a contact. Use after confirming the contact exists to remove it permanently. |
| `REPLY_IO_DELETE_EMAIL_ACCOUNT` | Delete Email Account | Tool to delete a specific email account. Use when you need to remove an existing email account identified by its ID. |
| `REPLY_IO_DELETE_SCHEDULE` | Delete Schedule | Tool to delete a schedule. Use after confirming the schedule exists to remove it permanently. |
| `REPLY_IO_DELETE_SEQUENCE` | Delete Sequence | Tool to delete a sequence. Use after confirming the sequence exists to remove it permanently. |
| `REPLY_IO_DELETE_USER` | Delete User | Tool to delete a user. Use after confirming the user exists to remove them permanently. |
| `REPLY_IO_GENERATE_ULID` | Generate ULID | Generate ULID |
| `REPLY_IO_GET_CONTACT_BY_ID` | Get Contact by ID | Tool to retrieve a contact by ID. Use when you have a contact ID and need detailed contact information. |
| `REPLY_IO_GET_CONTACT_STATUS` | Get Contact Status | Tool to get contact status. Use when you need to retrieve all current statuses for a contact. |
| `REPLY_IO_GET_CURRENT_USER` | Get Current User | Tool to get the current authenticated user's ID. Use when you need to verify API key validity or identify the current user. |
| `REPLY_IO_GET_DISCONNECTED_EMAIL_ACCOUNTS` | Reply.io Get Disconnected Email Accounts | Tool to list email accounts that are currently disconnected due to authentication or connection errors. Use when you need to identify and troubleshoot problematic email accounts. |
| `REPLY_IO_GET_SEQUENCE_BY_ID` | Get Sequence By ID | Tool to retrieve detailed information about a sequence by its ID. Use when you need to get comprehensive sequence details including settings, email accounts, and workflow steps. |
| `REPLY_IO_GET_SEQUENCE_CONTACTS_EXTENDED` | Get Sequence Contacts Extended | Tool to retrieve all contacts enrolled in a sequence with additional details. Use when you need to see contact engagement status, current step, or completion timestamps within a sequence. |
| `REPLY_IO_GET_SEQUENCE_STEP_BY_ID` | Get Sequence Step by ID | Tool to retrieve details of a specific sequence step. Use when you need to inspect step configuration including type, delays, execution mode, and type-specific settings. |
| `REPLY_IO_LIST_CONTACTS_BASIC` | List Contacts Basic | Tool to list contacts. Use when verifying API access and gathering contact IDs. |
| `REPLY_IO_LIST_EMAIL_ACCOUNTS` | Reply.io List Email Accounts | Tool to list all email accounts. Use when you need to retrieve email accounts page by page. |
| `REPLY_IO_LIST_LISTS` | Reply.io List Lists | Tool to list all contact lists. Use when you need to retrieve all available lists in your Reply.io account. |
| `REPLY_IO_LIST_SEQUENCES` | List Sequences | Tool to retrieve a paginated list of sequences. Use when you need to browse sequences with optional filtering by name. |
| `REPLY_IO_LIST_SEQUENCE_STEPS` | List Sequence Steps | Tool to retrieve all steps in a sequence. Use when you need to get the complete list of steps configured for a specific sequence. |
| `REPLY_IO_PAUSE_SEQUENCE` | Pause Sequence | Tool to pause a running sequence. Use when you need to temporarily stop a sequence from sending emails or executing steps. |
| `REPLY_IO_REMOVE_CONTACT_FROM_SEQUENCE` | Remove Contact From Sequence | Tool to remove a contact from a sequence. Use when you need to stop a contact from receiving further steps in a specific sequence. |
| `REPLY_IO_REMOVE_CONTACTS_FROM_SEQUENCE` | Bulk Remove Contacts from Sequence | Tool to bulk remove multiple contacts from a sequence at once. Use when you need to remove several contacts from a sequence efficiently in a single operation. |
| `REPLY_IO_SEARCH_CONTACTS` | Search Contacts by Email | Tool to search contacts by email. Use when you need to find existing contact IDs for update tests. |
| `REPLY_IO_SET_CONTACT_STATUS` | Set Contact Status | Tool to set the status of one or more contacts. Use when you need to update contact statuses in bulk. |
| `REPLY_IO_START_SEQUENCE` | Start Sequence | Tool to start a sequence. Use when you need to activate a sequence that is in New or Paused status. |
| `REPLY_IO_UPDATE_CONTACT` | Update Contact | Tool to update an existing contact's information. Use when you need to modify contact details. |
| `REPLY_IO_UPDATE_EMAIL_ACCOUNT` | Update Email Account | Tool to update an existing email account with custom SMTP/IMAP settings. Use when you need to modify email account configuration such as sender name, signature, server settings, or daily limits. |

## Supported Triggers

None listed.

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

The Reply io MCP server is an implementation of the Model Context Protocol that connects your AI agent to Reply io. It provides structured and secure access so your agent can perform Reply io 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 starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Reply io project
- Some knowledge of Python or Typescript

### 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).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Reply io.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

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

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only reply_io.
- The router checks the user's Reply io connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Reply io.
- This approach keeps things lightweight and lets the agent request Reply io tools only when needed during the conversation.
```python
# Create a Reply io Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["reply_io"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Reply io
const session = await composio.create(userId as string, {
  toolkits: ['reply_io'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Reply io. "
        "Help users perform Reply io operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Reply io. Help users perform Reply io operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

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

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

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

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["reply_io"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Reply io. "
        "Help users perform Reply io operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

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

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['reply_io'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Reply io. Help users perform Reply io operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

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

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\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

This was a starter code for integrating Reply io MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Reply io.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Reply io MCP Agent with another framework

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

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- [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.
- [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Reply io MCP?

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

### Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Reply io tools.

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

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

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