# How to integrate Teltel MCP with LlamaIndex

```json
{
  "title": "How to integrate Teltel MCP with LlamaIndex",
  "toolkit": "Teltel",
  "toolkit_slug": "teltel",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/teltel/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/teltel/framework/llama-index.md",
  "updated_at": "2026-05-12T10:28:06.806Z"
}
```

## Introduction

This guide walks you through connecting Teltel to LlamaIndex using the Composio tool router. By the end, you'll have a working Teltel agent that can retrieve all missed calls from today, list all sms messages from specific number, show teltel users added this week through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Teltel account through Composio's Teltel MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Teltel with

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

The Teltel MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Teltel account. It provides structured and secure access to your telecom data, so your agent can retrieve call logs, manage SMS messages, access user records, and handle inbound SMS events automatically.
- Comprehensive call log retrieval: Quickly fetch and filter detailed lists of your recent and historical calls, including duration, status, and time for easy reporting or analysis.
- SMS message management: Effortlessly access sent and received SMS logs, filter messages by sender, recipient, status, or date, and keep your communications organized.
- User directory synchronization: Retrieve up-to-date lists of all users in your Teltel account, making it simple to manage contact center agents or team members.
- Automated inbound SMS handling: Set up your agent to receive and process incoming SMS via webhook, so you never miss an important customer message or support request.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `TELTEL_CREATE_AUTODIALER_CUSTOM_STATUS` | Create Autodialer Custom Status | Tool to create a custom status for autodialer contacts. Use when you need to add a new status option that agents can use to categorize contacts in the Operator Dashboard. |
| `TELTEL_CREATE_CALL` | Create Call | Tool to create a call between two participants. Use when you need to initiate an outbound call connecting a caller to a destination number. |
| `TELTEL_CREATE_USER_STATUS` | Create User Status | Tool to create a user status in TelTel. Use when you need to add a new status option for users. |
| `TELTEL_DELETE_AUTODIALER_CUSTOM_STATUS` | Delete Autodialer Custom Status | Tool to delete an autodialer custom status by ID. Use when you need to remove a custom status from your autodialer configuration. |
| `TELTEL_DELETE_USER_STATUS` | Delete User Status | Tool to delete a user status by ID. Use when you need to remove an existing user status from TelTel. |
| `TELTEL_GET_ACCOUNT_BALANCE` | Get Account Balance | Tool to retrieve the account balance for your TelTel account. Use when you need to check available credit or account balance information. |
| `TELTEL_GET_CALL_LIST` | Get Call List | Tool to retrieve a list of calls with details (duration, time, status). Use when you need to filter and page through call records. |
| `TELTEL_GET_COUNTRY` | Get Country | Tool to retrieve country resource information by ID from TelTel. Use when you need to fetch details about a specific country for DID number provisioning. |
| `TELTEL_GET_SMS_LIST` | Get SMS List | Tool to retrieve a list of sent (outbox) or received (inbox) SMS messages from TelTel. Use when you need to filter or paginate through SMS message history. Supports filtering by date, sender, recipient, and message state. |
| `TELTEL_GET_USER_CID_GROUPS` | Get User Caller ID Groups | Tool to retrieve caller ID groups for a specific user. Use when you need to fetch the list of CID groups associated with a user account. |
| `TELTEL_GET_USERS_LIST` | Get Users List | Tool to retrieve a list of users from your TelTel account. Use when you need to page through or synchronize user records. |
| `TELTEL_LIST_AUTODIALER_ACTIONS` | List Autodialer Actions | Tool to retrieve the action history for an autodialer campaign. Use when you need to view the list of actions performed on a specific autodialer campaign. |
| `TELTEL_LIST_AUTODIALER_CONTACTS` | List Autodialer Contacts | Tool to retrieve the contact list for an autodialer campaign. Use when you need to view contacts, filter by phone number or start time, or paginate through campaign contacts. |
| `TELTEL_LIST_AUTODIALER_CUSTOM_STATUSES` | List Autodialer Custom Statuses | Tool to retrieve list of autodialer custom statuses. Use when you need to view all available custom statuses for autodialer campaigns. |
| `TELTEL_LIST_AUTO_DIALERS` | List Autodialer Campaigns | Tool to retrieve a list of autodialer campaigns from TelTel. Use when you need to view all autodialer campaigns and their details. |
| `TELTEL_LIST_AVAILABLE_COUNTRIES` | List Available Countries | Tool to get the list of countries where DID numbers are available for purchase. Use when you need to discover which countries support phone number provisioning or filter countries by pricing and features. |
| `TELTEL_LIST_COUNTRY_PRICE_GROUPS` | List Country Price Groups | Tool to retrieve phone number price groups available in a specific country. Use when you need to view pricing tiers or filter available phone number groups by country. |
| `TELTEL_LIST_DEVICES` | List Devices | Tool to retrieve a list of devices from your TelTel account. Use when you need to view all registered devices and their connection status. |
| `TELTEL_LIST_MY_NUMBERS` | List My Numbers | Tool to retrieve a list of phone numbers (DIDs) owned by the account. Use when you need to view all purchased phone numbers or filter by activation status, auto-renew settings, or SMS/voice support. |
| `TELTEL_LIST_ORDERS` | List DID Orders | Tool to retrieve a list of DID (phone number) orders from TelTel. Use when you need to check order status, view order history, or filter orders by specific criteria like status or type. |
| `TELTEL_LIST_USER_STATUSES` | List User Statuses | Tool to retrieve a list of all user statuses in TelTel. Use when you need to view available status options for users. |
| `TELTEL_LOOKUP_PHONE_NUMBER` | Lookup Phone Number | Tool to perform HLR (Home Location Register) lookup for phone numbers via TelTel API. Use when you need to verify phone number validity, check network status, or retrieve carrier information. Supports single or multiple phone numbers in one request. |
| `TELTEL_RECEIVE_INBOUND_SMS` | Receive Inbound SMS | Tool to process inbound SMS webhook data from TelTel. Use this to handle incoming SMS notifications that TelTel sends to your configured webhook URL. This action parses and validates the webhook payload, returning the SMS details in a structured format for further processing. Note: TelTel sends inbound SMS data via GET request with query parameters. Configure your webhook URL in TelTel account settings. |
| `TELTEL_SET_USER_STATUS` | Set User Status | Tool to set a user's status in TelTel. Use when you need to update a user's availability or activity status. |
| `TELTEL_UPDATE_AUTODIALER_CUSTOM_STATUS` | Update Autodialer Custom Status | Tool to update an autodialer custom status value by ID. Use when you need to rename or modify an existing custom status label. |
| `TELTEL_UPDATE_USER_STATUS` | Update User Status | Tool to update an existing user status in TelTel. Use when you need to modify the name, enabled state, or offline state of a user status. |

## Supported Triggers

None listed.

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

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

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

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 Teltel 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, teltel)
- 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 Teltel 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=["teltel"],
    )

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

  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 Teltel 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 Teltel
```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 Teltel, 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=["teltel"],
    )

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

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

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

## Related Toolkits

- [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools.
- [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations.
- [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates.
- [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates.
- [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. It helps businesses automate support and streamline interactions through natural, voice-powered conversations.
- [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code.
- [Botstar](https://composio.dev/toolkits/botstar) - BotStar is a comprehensive chatbot platform for designing, developing, and training chatbots visually on Messenger and websites. It helps businesses automate conversations and customer interactions without coding.
- [Callerapi](https://composio.dev/toolkits/callerapi) - CallerAPI is a white-label caller identification platform for branded caller ID and fraud prevention. It helps businesses boost customer trust while stopping spam, fraud, and robocalls.
- [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources.
- [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates.
- [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster.
- [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment.
- [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support.
- [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach.
- [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback.
- [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses.

## Frequently Asked Questions

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

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

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

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

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