# How to integrate Unisender MCP with LlamaIndex

```json
{
  "title": "How to integrate Unisender MCP with LlamaIndex",
  "toolkit": "Unisender",
  "toolkit_slug": "unisender",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/unisender/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/unisender/framework/llama-index.md",
  "updated_at": "2026-03-29T06:54:16.935Z"
}
```

## Introduction

This guide walks you through connecting Unisender to LlamaIndex using the Composio tool router. By the end, you'll have a working Unisender agent that can send an sms campaign to new signups, create a new email list segment, check status of yesterday's email campaign through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Unisender account through Composio's Unisender MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Unisender with

- [OpenAI Agents SDK](https://composio.dev/toolkits/unisender/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/unisender/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/unisender/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/unisender/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/unisender/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/unisender/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/unisender/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/unisender/framework/cli)
- [Google ADK](https://composio.dev/toolkits/unisender/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/unisender/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/unisender/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/unisender/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/unisender/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 Unisender
- Connect LlamaIndex to the Unisender MCP server
- Build a Unisender-powered agent using LlamaIndex
- Interact with Unisender 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 Unisender MCP server, and what's possible with it?

The Unisender MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Unisender account. It provides structured and secure access so your agent can perform Unisender operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `UNISENDER_CHECK_EMAIL` | Check Email Status | Tool to check the delivery status of emails sent via sendEmail method. Use when you need to verify email delivery status by email IDs. Statuses are stored for approximately one month. Rate limited to 300 requests per 60 seconds. |
| `UNISENDER_CREATE_EMAIL_TEMPLATE` | Create Email Template | Tool to create a new email template for mass campaigns in UniSender. Use when you need to create a reusable email template with customizable title, subject, body content, and sender information. |
| `UNISENDER_CREATE_FIELD` | Create Field | Tool to create a new custom field for contact data in UniSender. Use when you need to add a custom field that can store additional contact information and be used in email message substitutions. |
| `UNISENDER_CREATE_LIST` | Create List | Tool to create a new contact list for organizing thematic email campaigns in UniSender. Use when you need to create a new mailing list with a unique title. The list title must be unique within the account. |
| `UNISENDER_CREATE_SUBSCRIBER_NOTE` | Create Subscriber Note | Tool to create a note for a subscriber contact in UniSender. Use when you need to add a new note to a subscriber's profile. Notes created via API have an 'origin' field set to 'api'. |
| `UNISENDER_DELETE_FIELD` | Delete Field | Tool to remove a custom field from the Unisender system. Use when you need to permanently delete a custom field and all its associated contact data. |
| `UNISENDER_DELETE_LIST` | Delete List | Tool to permanently delete a contact list from your UniSender account. Use when you need to remove a mailing list by its ID. |
| `UNISENDER_DELETE_SUBSCRIBER_NOTE` | Delete Subscriber Note | Tool to delete a subscriber note from UniSender by its ID. Use when you need to remove a note associated with a subscriber/contact from the system. |
| `UNISENDER_DELETE_TAG` | Delete Tag | Tool to delete a tag by its ID and remove it from all associated contacts. Use when you need to remove a tag from your UniSender account. |
| `UNISENDER_DELETE_TEMPLATE` | Delete Template | Tool to remove a template from the UniSender account. Use when you need to permanently delete a template by its ID. |
| `UNISENDER_EXCLUDE_CONTACT_FROM_LISTS` | Exclude Contact from Lists | Tool to remove contacts from specified lists or all lists in UniSender. Use when you need to exclude a contact (email or phone) from mailing lists. Unlike unsubscribe, exclude actually removes the contact from lists, allowing them to be re-added later using the subscribe method. Recommended when subscription management is performed by sender's initiative. |
| `UNISENDER_EXPORT_CONTACTS` | Export Contacts | Tool to export contact data from UniSender lists for synchronization. Use when you need to export email addresses, phone numbers, and custom fields from lists. This method works asynchronously - the response contains a task_uuid for tracking export status. |
| `UNISENDER_GET_CAMPAIGNS` | Get Campaigns | Tool to retrieve list of campaigns from Unisender within a specified date range. Use when you need to fetch email campaign information with optional filtering by date and pagination support. Returns up to 10,000 campaigns per request. |
| `UNISENDER_GET_CAMPAIGN_STATUS` | Get Campaign Status | Tool to check the current status of a campaign in UniSender. Use when you need to verify campaign progress or completion status. Returns detailed status information including creation time and start time. |
| `UNISENDER_GET_CONTACT` | Get Contact | Tool to get information about a single contact from UniSender. Use when you need to retrieve detailed contact data including email/phone status, custom fields, list memberships, and engagement statistics. Either email or contact_id must be provided. |
| `UNISENDER_GET_CONTACT_FIELD_VALUES` | Get Contact Field Values | Tool to retrieve custom field values for a specific contact identified by email address. Use when you need to get additional field data associated with a contact. You can optionally specify which fields to retrieve by providing field IDs. |
| `UNISENDER_GET_FIELDS` | Get Fields | Tool to retrieve all custom user-defined fields for contact personalization and data management. Use when creating integrations to map fields between systems or to retrieve available custom fields for contacts. |
| `UNISENDER_GET_LISTS` | Get Lists | Tool to retrieve all existing mailing lists associated with the account. Use when you need to get list IDs and titles before sending emails or SMS to a list, or to display available contact lists. |
| `UNISENDER_GET_MESSAGES` | Get Messages | Tool to retrieve list of all messages with body and attachments. Use when you need complete message information including content and attachments, unlike listMessages which returns only metadata. |
| `UNISENDER_GET_SENDER_DOMAIN_LIST` | Get Sender Domain List | Tool to retrieve information about sender domains and their DKIM status. Use when you need to check which domains are registered for sending emails and their verification status. |
| `UNISENDER_GET_TAGS` | Get Tags | Tool to retrieve all custom tags/labels for contact segmentation. Use when you need to list all available tags in the Unisender account. |
| `UNISENDER_GET_TEMPLATE` | Get Template | Tool to retrieve detailed information about a specific email template by its ID. Use when you need to fetch template details including metadata, content, creation details, and formatting information. |
| `UNISENDER_GET_TEMPLATES` | Get Templates | Tool to retrieve list of all templates with full content including body. Use when you need complete template information including raw_body and body fields, unlike listTemplates which returns templates without body content. |
| `UNISENDER_IMPORT_CONTACTS_BULK` | Import Contacts (Bulk) | Tool to bulk import contacts to UniSender with maximum 500 contacts per call. Use when you need to import multiple contacts at once with their fields, list subscriptions, and tags. Supports creating new contacts, updating existing ones, and managing list subscriptions. UniSender automatically validates emails and filters spam-traps. |
| `UNISENDER_CHECK_IF_CONTACT_IS_IN_LISTS` | Check if Contact is in Lists | Tool to check if a contact exists in specified mailing lists based on and/or conditions. Use when you need to verify whether a contact is a member of specific lists. The condition parameter allows checking if the contact is in all lists (and) or at least one list (or). |
| `UNISENDER_LIST_MESSAGES` | List Messages | Tool to list all messages without body and attachments. Use when you need to browse available messages created via API or web interface. |
| `UNISENDER_LIST_TEMPLATES` | List Templates | Tool to list email templates without body content. Use when you need to browse available templates created via API or web interface. |
| `UNISENDER_SUBSCRIBE_CONTACT_TO_LISTS` | Subscribe Contact to Lists | Tool to add contacts to one or multiple mailing lists with optional tags and field values. Use when you need to subscribe a contact (email and/or phone) to Unisender lists. This method adds contacts individually and can override existing contact data based on the overwrite parameter. Contacts previously excluded can be re-added using this action. |
| `UNISENDER_UNSUBSCRIBE_CONTACT` | Unsubscribe Contact | Tool to unsubscribe contacts from mailing lists in UniSender. Use when a contact initiates opt-out from campaigns. This marks contacts as 'unsubscribed' rather than excluding them - the active status can only be restored by the contact clicking an activation link. |
| `UNISENDER_UPDATE_EMAIL_TEMPLATE` | Update Email Template | Tool to update an existing email template for mass campaigns. Use when you need to modify template properties like title, subject, body content, sender information, or language settings. Only the fields you specify will be updated. |
| `UNISENDER_UPDATE_FIELD` | Update Field | Tool to modify parameters of an existing custom field in UniSender. Use when you need to change field properties like name, display name, type, visibility, or display position. |
| `UNISENDER_UPDATE_LIST` | Update List | Tool to update the parameters of an existing contact list in UniSender. Use when you need to change the title, pre-subscription URL, or post-subscription URL of an existing mailing list. |
| `UNISENDER_UPDATE_SUBSCRIBER_NOTE` | Update Subscriber Note | Tool to update the content of an existing subscriber note in UniSender. Use when you need to edit or modify the content of a previously created note attached to a subscriber. |

## Supported Triggers

None listed.

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

The Unisender MCP server is an implementation of the Model Context Protocol that connects your AI agent to Unisender. It provides structured and secure access so your agent can perform Unisender 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 Unisender account and project
- Basic familiarity with async Python/Typescript

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

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 Unisender 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, unisender)
- 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 Unisender 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=["unisender"],
    )

    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 Unisender actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Unisender 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: ["unisender"],
    },
  );

  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 Unisender 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 Unisender
```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 Unisender, 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=["unisender"],
    )

    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 Unisender actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Unisender 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: ["unisender"],
    },
  );

  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 Unisender 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 Unisender to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Unisender 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 Unisender MCP Agent with another framework

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

## Related Toolkits

- [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing.
- [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages.
- [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections.
- [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach.
- [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease.
- [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic.
- [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns.
- [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active.
- [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place.
- [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES.
- [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere.
- [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools.
- [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools.
- [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes.
- [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management.
- [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals.
- [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams.
- [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience.
- [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs.
- [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics.

## Frequently Asked Questions

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

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

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

Yes, absolutely. You can configure which Unisender 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 Unisender 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)