# How to integrate Customerio MCP with LlamaIndex

```json
{
  "title": "How to integrate Customerio MCP with LlamaIndex",
  "toolkit": "Customerio",
  "toolkit_slug": "customerio",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/customerio/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/customerio/framework/llama-index.md",
  "updated_at": "2026-05-12T10:08:00.753Z"
}
```

## Introduction

This guide walks you through connecting Customerio to LlamaIndex using the Composio tool router. By the end, you'll have a working Customerio agent that can list all segments in your workspace, get delivery metrics for last week's emails, show all people in vip customer segment through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Customerio account through Composio's Customerio MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Customerio with

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

The Customerio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Customer.io account. It provides structured and secure access to your customer engagement workspace, allowing your agent to send targeted communications, manage segments, retrieve messaging analytics, and automate customer data management on your behalf.
- Targeted message analytics and tracking: Retrieve detailed lists of messages sent, including delivery metrics, to monitor campaign performance and engagement.
- Segment discovery and membership management: Let your agent fetch all segments, get details for a specific segment, and list all customers in a segment for precise audience targeting.
- Integration and webhook management: Have your agent list and review all integrations and webhooks in your workspace to streamline system connectivity and reporting.
- Customer profile suppression: Direct your agent to permanently suppress (delete and block) customer profiles, ensuring compliance and data privacy.
- Collection metadata retrieval: Retrieve up-to-date details for all collections in your workspace, keeping your AI-powered workflows and automations in sync with your data sources.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CUSTOMERIO_ADD_PERSON_TO_GROUP` | Add Person to Group | Tool to add people to a group in Customer.io. Groups represent objects like companies, accounts, or projects that people belong to. Use when you need to establish relationships between people and organizational entities. |
| `CUSTOMERIO_CREATE_ALIAS` | Create Profile Alias | Tool to create an alias to merge multiple profiles in Customer.io. Use when you need to support multiple identifiers for a single person. The alias operation moves all data from the previous_id profile to the user_id profile, consolidating them into a single canonical profile. |
| `CUSTOMERIO_CUSTOMER_IO_SUPPRESS_PERSON` | Suppress Customer Profile | Suppress a customer profile to permanently delete it and prevent re-adding with the same identifier. IMPORTANT: This action requires Track API credentials (Basic Auth with siteId:apiKey), not App API credentials. Suppression also deletes the customer profile - you don't need to call a separate delete endpoint. Use this for GDPR/CCPA compliance requests. The operation is irreversible and prevents any future attempts to re-add a person with the same identifier (email or ID). |
| `CUSTOMERIO_GET_INTEGRATIONS` | Get Integrations | Tool to retrieve a list of integrations in your workspace. Use when you need to discover configured integrations. |
| `CUSTOMERIO_GET_MESSAGES` | Get Messages | Tool to retrieve a list of messages sent from your workspace. Use when you need paginated delivery metrics for messages, e.g., list email messages delivered between two timestamps. |
| `CUSTOMERIO_GET_SEGMENT_DETAILS` | Get Segment Details | Tool to retrieve details of a specific segment. Use after identifying the segment ID from list segments. |
| `CUSTOMERIO_GET_SEGMENT_MEMBERSHIP` | Get Segment Membership | Tool to retrieve people in a specific segment. Use when you need to page through segment membership after identifying segment ID. |
| `CUSTOMERIO_GET_SEGMENTS` | Get Segments | Tool to retrieve a list of segments in your workspace. Use when you need to fetch all segments after configuring segment rules. |
| `CUSTOMERIO_GET_TRIGGER` | Get Trigger | Retrieves details about a specific API-triggered broadcast, including trigger ID, campaign ID, creation timestamp, recipient filter criteria, and personalization data. Use this after triggering a broadcast to verify its configuration and check the data used for message personalization. |
| `CUSTOMERIO_GET_TRIGGERS` | Get Broadcast Triggers | Retrieve all API trigger instances for a specific broadcast/campaign. Returns trigger metadata including IDs, creation timestamps, and processing status. Use after triggering a broadcast to list all its trigger executions. |
| `CUSTOMERIO_GET_WEBHOOKS` | Get Customer.io Workspace Webhooks | Retrieves all reporting webhook configurations from the Customer.io workspace. Reporting webhooks send event notifications (message sent, opened, clicked, etc.) to your specified endpoints. Use this to list all configured webhooks and their settings including subscribed events, endpoints, and status. Returns an empty list if no webhooks are configured. |
| `CUSTOMERIO_IDENTIFY_PERSON` | Identify Person | Tool to identify a person and assign traits to them in Customer.io. Creates a new person profile if it doesn't exist, or updates an existing one. Use when adding new users, updating user profiles, or tracking anonymous visitors. Either user_id or anonymous_id must be provided. |
| `CUSTOMERIO_LIST_COLLECTIONS` | List Collections | Tool to list all Collections metadata. Use when you need to retrieve current details of each Collection in your workspace. |
| `CUSTOMERIO_LIST_IP_ADDRESSES` | List IP Addresses | Tool to retrieve the list of IP addresses used by Customer.io for sending messages. Use when you need to allowlist or configure firewall rules for Customer.io's sending infrastructure. |
| `CUSTOMERIO_LIST_NEWSLETTERS` | List Newsletters | Tool to list all newsletters. Use when paginating through newsletter metadata. |
| `CUSTOMERIO_LIST_SNIPPETS` | List Snippets | Tool to list all snippets in your workspace. Use when you need to retrieve all reusable content snippets for templating or dynamic content insertion. |
| `CUSTOMERIO_LIST_TRANSACTIONAL_MESSAGES` | List Transactional Messages | Lists all transactional message templates in your Customer.io workspace. Returns the ID and name (trigger name) for each template. Use this when you need to discover available transactional message templates or retrieve their IDs for sending messages via the API. |
| `CUSTOMERIO_SEND_BATCH` | Send Batch CDP Calls | Send multiple CDP calls (identify, track, page, screen, group, alias) in a single batch request. Use this to efficiently send multiple events or profile updates in one API call. The batch endpoint supports up to 500KB total with 32KB per individual call. Each call in the batch can be a different type (identify, track, page, screen, group, or alias). Requirements by call type: - identify/track/page/screen: Require userId or anonymousId - group: Requires groupId (and userId or anonymousId) - track: Requires event name - alias: Requires userId and previousId Note: This action uses the CDP API base URL (https://cdp.customer.io/v1) which differs from the Track API base URL used by some other Customer.io actions. |
| `CUSTOMERIO_TRACK_EVENT` | Track Event | Tool to send an event associated with a person in Customer.io. Records actions users take, along with properties that describe the action. Use when you need to track user behavior, conversions, or custom events for segmentation and campaigns. |
| `CUSTOMERIO_TRACK_PAGE` | Track Page View | Tool to track page view events for website visitors in Customer.io. Use when recording user navigation or page impressions on your website. IMPORTANT: This action requires CDP API credentials (Bearer token), not Track API or App API credentials. Either user_id or anonymous_id must be provided to identify the viewer. Include properties like url, title, and path to enrich analytics and segmentation capabilities. |
| `CUSTOMERIO_TRACK_SCREEN` | Track Screen View | Track mobile screen views in Customer.io for analytics and user journey tracking. Records when a user views a screen in your mobile app. Use this when you need to: - Track user navigation patterns in mobile apps - Record screen views for engagement analytics - Trigger workflows based on specific screen visits - Build user journey maps based on screen flow Requirements: - Provide either userId (for known users) or anonymousId (for anonymous users) - Screen name is required to identify which screen was viewed - Optionally include properties for additional context (platform, category, etc.) Note: This endpoint uses the CDP API (cdp.customer.io), not the standard App API. |
| `CUSTOMERIO_TRIGGER_BROADCAST` | Trigger Broadcast | Manually trigger a Customer.io broadcast/campaign to send messages to a defined audience. Use this when you need to: - Send a pre-configured broadcast to specific recipients (by ID or email) - Override the broadcast's default UI-defined audience with custom filtering - Provide personalization data for Liquid template variables - Send individualized content using per_user_data Requirements: - broadcast_id: Must be a valid broadcast ID from Customer.io (find in broadcast's Triggering Details) - Audience: Provide exactly ONE of: recipients, ids, emails, per_user_data, or data_file_url Rate Limits: This endpoint allows one request every 10 seconds per broadcast. |
| `CUSTOMERIO_UNSUBSCRIBE_DELIVERY` | Unsubscribe from Delivery | Tool to handle custom unsubscribe requests for email deliveries in Customer.io. Use when you need to unsubscribe a person from emails and attribute the action to a specific delivery. IMPORTANT: This action requires Track API credentials (Basic Auth with siteId:apiKey), not App API credentials. The unsubscribe action sets the person's unsubscribed attribute to true. |

## Supported Triggers

None listed.

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

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

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

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 Customerio 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, customerio)
- 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 Customerio 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=["customerio"],
    )

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

  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 Customerio 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 Customerio
```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 Customerio, 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=["customerio"],
    )

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

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

- [ChatGPT](https://composio.dev/toolkits/customerio/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/customerio/framework/antigravity)
- [OpenAI Agents SDK](https://composio.dev/toolkits/customerio/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/customerio/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/customerio/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/customerio/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/customerio/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/customerio/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/customerio/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/customerio/framework/cli)
- [Google ADK](https://composio.dev/toolkits/customerio/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/customerio/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/customerio/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/customerio/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/customerio/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.
- [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.
- [Doppler marketing automation](https://composio.dev/toolkits/doppler_marketing_automation) - Doppler marketing automation is a platform for creating, sending, and tracking email campaigns. It helps you automate marketing workflows and manage subscriber lists for better engagement.

## Frequently Asked Questions

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

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

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

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

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