# How to integrate Enginemailer MCP with LlamaIndex

```json
{
  "title": "How to integrate Enginemailer MCP with LlamaIndex",
  "toolkit": "Enginemailer",
  "toolkit_slug": "enginemailer",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/enginemailer/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/enginemailer/framework/llama-index.md",
  "updated_at": "2026-05-12T10:10:24.662Z"
}
```

## Introduction

This guide walks you through connecting Enginemailer to LlamaIndex using the Composio tool router. By the end, you'll have a working Enginemailer agent that can add new subscriber to newsletter list, pause tomorrow's scheduled marketing campaign, export email delivery report from last week through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Enginemailer account through Composio's Enginemailer MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Enginemailer with

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

## TL;DR

Here's what you'll learn:
- Set your OpenAI and Composio API keys
- Install LlamaIndex and Composio packages
- Create a Composio Tool Router session for Enginemailer
- Connect LlamaIndex to the Enginemailer MCP server
- Build a Enginemailer-powered agent using LlamaIndex
- Interact with Enginemailer through natural language

## What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.
Key features include:
- ReAct Agent: Reasoning and acting pattern for tool-using agents
- MCP Tools: Native support for Model Context Protocol
- Context Management: Maintain conversation context across interactions
- Async Support: Built for async/await patterns

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

The Enginemailer MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Enginemailer account. It provides structured and secure access to your email marketing platform, so your agent can perform actions like creating campaigns, managing subscriber lists, exporting reports, and sending personalized email campaigns on your behalf.
- Campaign creation and scheduling: Direct your agent to set up new email campaigns, configure content, and schedule delivery to your audience.
- Subscriber management: Have your agent add new subscribers to your lists, including custom fields and segmentation for targeted outreach.
- Instant campaign delivery and controls: Command your agent to send campaigns immediately or pause scheduled campaigns for last-minute adjustments.
- Campaign monitoring and reporting: Let your agent export detailed email campaign reports as CSV files and check the status of ongoing exports.
- Audience segmentation and subcategory retrieval: Guide your agent to fetch subcategories and organize recipients for more personalized and effective campaigns.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ENGINEMAILER_ACTIVATE_SUBSCRIBER` | Activate Subscriber | Tool to activate an inactive subscriber in EngineMailer. Use when you need to reactivate a subscriber that was previously deactivated either through the API or manually. |
| `ENGINEMAILER_ADD_UPDATE_SUBSCRIBER` | Add or Update Subscriber | Tool to add or update a subscriber with custom fields via N8N integration. Use when you need to create a new subscriber or update an existing one in the EngineMailer system. |
| `ENGINEMAILER_BATCH_UPDATE_STATUS` | Check Batch Update Status | Tool to check the status of a batch subscriber update operation. Use when you need to verify if a batch update job has completed or is still processing. |
| `ENGINEMAILER_BATCH_UPDATE_SUBSCRIBERS` | Batch Update Subscribers | Tool to add or update multiple subscribers with custom fields in a single batch operation. Use when you need to create or update multiple subscribers efficiently. Subscribers that fail validation are removed from processing automatically. |
| `ENGINEMAILER_CHECK_EXPORT_STATUS_V2` | Check Export Status V2 | Tool to check status of a previously requested CSV report export. Use after initiating an export to poll for completion. Large exports may take significant time; poll repeatedly until status indicates readiness before consuming the export data. |
| `ENGINEMAILER_CONNECT` | Test API Connection | Tool to test API connection and verify authentication. Use when you need to validate API credentials or check connectivity. |
| `ENGINEMAILER_CREATE_CAMPAIGN` | Create Campaign | Tool to create a new email campaign. Use when you need to configure and schedule a campaign before sending. Set trackOpens and trackClicks at creation; these flags cannot retroactively affect already-delivered messages. |
| `ENGINEMAILER_DELETE_CAMPAIGN` | Delete Campaign | Tool to delete an undelivered email campaign. Use when you need to remove a campaign that has not been sent yet. |
| `ENGINEMAILER_DELETE_RECIPIENT_LIST` | Delete Recipient List | Tool to delete an existing recipient list from a targeted campaign. Use when you need to remove a specific recipient list from a campaign. |
| `ENGINEMAILER_DELETE_SUBSCRIBER` | Delete Subscriber | Tool to remove a subscriber from the system by email address. Use when you need to permanently delete a subscriber's record. |
| `ENGINEMAILER_EXPORT_CSV_REPORT_V2` | Export CSV Report V2 | Tool to export a transactional email report as CSV. Initiates an async export within a specific date range (max past 60 days); check readiness via ENGINEMAILER_CHECK_EXPORT_STATUS_V2 before using the export. |
| `ENGINEMAILER_FIND_SUBSCRIBER` | Find Subscriber | Tool to find a subscriber by email address via N8N integration. Use when you need to search for and retrieve subscriber information from the EngineMailer system. |
| `ENGINEMAILER_GET_GETCUSTOMFIELD` | Get Custom Field List | Tool to retrieve the list of custom fields configured for subscribers. Use when you need to discover available custom fields for subscriber management. |
| `ENGINEMAILER_GET_LISTCAMPAIGN` | Get List Campaign | Tool to get a list of undelivered campaigns. Use when you need to fetch campaigns awaiting delivery. |
| `ENGINEMAILER_GET_NEW_SUBSCRIBERS` | Get New Subscribers | Tool to retrieve new subscribers with optional filtering by source, form, page, or popup. Use when you need to fetch recently added subscribers for synchronization or reporting workflows. |
| `ENGINEMAILER_GET_SUBCATEGORY` | Get Subcategories | Tool to retrieve subcategories for a given category. Use when you need to list or choose subcategories after selecting a category. |
| `ENGINEMAILER_GET_SUBSCRIBER` | Get Subscriber | Tool to retrieve subscriber information by email address. Use when you need to fetch details about a specific subscriber including their custom fields. |
| `ENGINEMAILER_GET_SUBSCRIBER_AUTORESPONDER_COMPLETED` | Get Subscriber Autoresponder Completed | Tool to retrieve subscribers who completed autoresponders with optional filtering by autoresponder ID. Use when you need to fetch completion events for autoresponders, optionally filtered by specific autoresponder or polling for new events since a timestamp. |
| `ENGINEMAILER_GET_SUBSCRIBER_AUTORESPONDER_TRIGGERED` | Get Subscriber Autoresponder Triggered | Tool to retrieve subscribers who triggered autoresponders with optional filtering by autoresponder ID. Use when you need to fetch trigger events for autoresponders, optionally filtered by specific autoresponder or polling for new events since a timestamp. |
| `ENGINEMAILER_GET_SUBSCRIBERS_DELETED` | Get Deleted Subscribers | Tool to retrieve deleted subscribers since last polling date. Use when you need to track or sync subscribers who have been removed from the system. |
| `ENGINEMAILER_GET_SUBSCRIBERS_MODIFIED` | Get Subscribers Modified | Tool to retrieve modified subscribers since last polling date with optional limit. Use when you need to fetch recently modified subscribers for synchronization or polling workflows. |
| `ENGINEMAILER_GET_SUBSCRIBERS_TAGGED` | Get Subscribers Tagged | Tool to retrieve subscribers who were tagged with optional filtering by subcategory. Use when you need to fetch tagged subscribers for synchronization or reporting workflows. |
| `ENGINEMAILER_GET_SUBSCRIBERS_UNTAGGED` | Get Untagged Subscribers | Tool to retrieve subscribers who were untagged from subcategories. Use when you need to track or sync subscribers who have had tags removed, with optional filtering by subcategory and polling date. |
| `ENGINEMAILER_GET_UNSUBSCRIBE` | Get Unsubscribe Events | Tool to retrieve unsubscribe events with optional filtering by campaign or autoresponder. Use when you need to fetch unsubscribe data for reporting, synchronization, or compliance workflows. |
| `ENGINEMAILER_INSERT_SUBSCRIBER` | Insert Subscriber | Tool to add a new subscriber with optional custom fields. Use when registering a user to a specific mailing list after verifying their email. |
| `ENGINEMAILER_LIST_AUTORESPONDERS` | List Autoresponders | Tool to retrieve a list of all autoresponders. Use when you need to fetch available autoresponders configured in the system. |
| `ENGINEMAILER_LIST_CAMPAIGNS` | List Campaigns | Tool to retrieve a list of all campaigns. Use when you need to fetch all campaigns from the system. |
| `ENGINEMAILER_LIST_FORMS` | List Forms | Tool to retrieve a list of available forms in Enginemailer. Use when you need to discover forms for n8n integration or workflow configuration. |
| `ENGINEMAILER_LIST_PAGES` | List Pages | Tool to retrieve a list of all pages. Use when you need to fetch available pages. |
| `ENGINEMAILER_LIST_POPUPS` | List Popups | Tool to retrieve a list of popups from Enginemailer. Use when you need to fetch available popups for n8n workflows. |
| `ENGINEMAILER_LIST_TEMPLATES` | List Templates | Tool to retrieve a list of all email templates. Use when you need to fetch available email templates for campaigns. |
| `ENGINEMAILER_PAUSE_CAMPAIGN` | Pause Campaign | Tool to pause a scheduled email campaign. Use when you need to halt a campaign before sending to apply updates or adjust schedule. |
| `ENGINEMAILER_POST_UPDATECATEGORY` | Create/Update Category | Tool to create or update a category for subscriber segmentation. Use when organizing subscribers by common interests for targeted email marketing. |
| `ENGINEMAILER_POST_UPDATE_SUBSCRIBER` | Update Subscriber | Tool to update data for an existing subscriber in EngineMailer. Use when you need to modify subscriber information such as custom fields or subcategory assignments. |
| `ENGINEMAILER_SEND_CAMPAIGN` | Send Campaign | Tool to send an email campaign immediately. Use when the campaign exists, has at least one recipient, and is not scheduled or already delivered. E.g., 'Send campaign 123 now'. |
| `ENGINEMAILER_TAG_TO_SUBCATEGORY` | Tag Subscriber to Subcategory | Tool to tag a subscriber to a specific subcategory via N8N API endpoint. Use when you need to categorize or organize subscribers by assigning them to a subcategory. |
| `ENGINEMAILER_UNSUBSCRIBE` | Unsubscribe (N8N) | Tool to unsubscribe a subscriber via N8N API endpoint. Use when you need to remove a subscriber from the mailing list using the N8N integration endpoint. |
| `ENGINEMAILER_UNSUBSCRIBE_SUBSCRIBER` | Unsubscribe Subscriber | Tool to unsubscribe a subscriber from the email list. Use when a user requests to be removed from the mailing list or to comply with unsubscribe requests. |

## Supported Triggers

None listed.

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

The Enginemailer MCP server is an implementation of the Model Context Protocol that connects your AI agent to Enginemailer. It provides structured and secure access so your agent can perform Enginemailer 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:
- Python 3.8/Node 16 or higher installed
- A Composio account with the API key
- An OpenAI API key
- A Enginemailer account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Enginemailer

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

```typescript
npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv
```

### 3. Set environment variables

Create a .env file in your project root:
These credentials will be used to:
- Authenticate with OpenAI's GPT-5 model
- Connect to Composio's Tool Router
- Identify your Composio user session for Enginemailer access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")
```

```typescript
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");
```

### 6. Create a Tool Router session and build the agent function

What's happening here:
- We create a Composio client using your API key and configure it with the LlamaIndex provider
- We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, enginemailer)
- The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
- LlamaIndex will connect to this endpoint to dynamically discover and use the available Enginemailer tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["enginemailer"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Enginemailer actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Enginemailer actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["enginemailer"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Enginemailer actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}
```

### 8. Define the main entry point

What's happening here:
- We're orchestrating the entire application flow
- The agent gets built with proper error handling
- Then we kick off the interactive chat loop so you can start talking to Enginemailer
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Enginemailer, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["enginemailer"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Enginemailer actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Enginemailer actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["enginemailer"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Enginemailer actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();
```

## Conclusion

You've successfully connected Enginemailer to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Enginemailer tools through an MCP endpoint
- LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
- The agent becomes more capable without increasing prompt size
- Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

## How to build Enginemailer MCP Agent with another framework

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

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- [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.
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- [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.
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- [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.
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## Frequently Asked Questions

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

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

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

Yes, you can. LlamaIndex 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 Enginemailer tools.

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

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

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