# How to integrate Emailable MCP with Autogen

```json
{
  "title": "How to integrate Emailable MCP with Autogen",
  "toolkit": "Emailable",
  "toolkit_slug": "emailable",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/emailable/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/emailable/framework/autogen.md",
  "updated_at": "2026-05-12T10:10:12.179Z"
}
```

## Introduction

This guide walks you through connecting Emailable to AutoGen using the Composio tool router. By the end, you'll have a working Emailable agent that can check if this email address is valid, verify a list of emails before newsletter send, get your emailable account credit balance through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Emailable account through Composio's Emailable MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Emailable with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Emailable
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Emailable tools
- Run a live chat loop where you ask the agent to perform Emailable operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

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

The Emailable MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Emailable account. It provides structured and secure access to your email verification services, so your agent can perform actions like real-time email validation, bulk batch checks, account monitoring, and verification status tracking on your behalf.
- Instant email address verification: Ask your agent to check if a single email address is valid, risky, or deliverable before you send that important message.
- Bulk batch email validation: Have the agent verify thousands of email addresses at once for newsletters, campaigns, or CRM imports, ensuring high deliverability rates.
- Batch job status monitoring: Let your agent track the progress and results of ongoing or completed batch verification jobs for timely follow-up actions.
- Account status and credit checks: Retrieve your Emailable account details, including owner info and available credits, to make sure you never run out of verification capacity.
- Seamless OAuth onboarding: Initiate the OAuth flow to securely grant your agent access to Emailable whenever needed, all without manual credential handling.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `EMAILABLE_GET_ACCOUNT_INFO` | Get Account Info | Tool to retrieve account information including owner email and available credits. Use when you need to confirm account status before sending email verifications. |
| `EMAILABLE_GET_BATCH_STATUS` | Get Batch Status | Tool to get the status and results of a batch verification job. Use after submitting a batch to check its progress. |
| `EMAILABLE_O_AUTH_AUTHORIZE` | Build OAuth Authorization URL | Build an OAuth 2.0 authorization URL for the Emailable authorization code flow. Returns a URL to redirect users to for authorization. Upon successful authorization, users are redirected to your redirect_uri with an authorization code (valid for 10 minutes) that can be exchanged for access tokens. |
| `EMAILABLE_VERIFY_BATCH_EMAILS` | Verify Batch Emails | Submit a batch of email addresses for asynchronous verification. Returns a batch ID immediately. Use this for bulk email validation (2 to 50,000 emails). For single emails, use EMAILABLE_VERIFY_EMAIL instead. The batch is processed asynchronously - use EMAILABLE_GET_BATCH_STATUS with the returned batch ID to check progress and retrieve verification results. |
| `EMAILABLE_VERIFY_EMAIL` | Verify Email | Tool to verify a single email address and return detailed results. Use when you need to check email deliverability and risk. |

## Supported Triggers

None listed.

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

The Emailable MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Emailable. Instead of manually wiring Emailable APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Emailable account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Emailable via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Emailable connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Emailable tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Emailable session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["emailable"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Emailable tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Emailable assistant agent with MCP tools
    agent = AssistantAgent(
        name="emailable_assistant",
        description="An AI assistant that helps with Emailable operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Emailable tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Emailable related question or task to the agent.\n")

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

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

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Emailable session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["emailable"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Emailable assistant agent with MCP tools
        agent = AssistantAgent(
            name="emailable_assistant",
            description="An AI assistant that helps with Emailable operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

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

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

## Conclusion

You now have an Autogen assistant wired into Emailable through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Emailable, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Emailable MCP Agent with another framework

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

## Related Toolkits

- [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure.
- [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms.
- [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place.
- [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.
- [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses.
- [Alchemy](https://composio.dev/toolkits/alchemy) - Alchemy is a blockchain development platform offering APIs and tools for Ethereum apps. It simplifies building and scaling Web3 projects with robust infrastructure.
- [Algolia](https://composio.dev/toolkits/algolia) - Algolia is a hosted search API that powers lightning-fast, relevant search experiences for web and mobile apps. It helps developers deliver instant, typo-tolerant, and scalable search without complex infrastructure.
- [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction.
- [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting.
- [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache.
- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

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

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

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

Yes, you can. Autogen 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 Emailable tools.

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

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

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