How to integrate Retellai MCP with LlamaIndex

This guide walks you through connecting Retellai to LlamaIndex using the Composio tool router. By the end, you'll have a working Retellai agent that can list all phone numbers linked to your account, retrieve call details for a specific agent this week, buy a new phone number with area code 415 through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Retellai account through Composio's Retellai MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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RetellAI is a platform for capturing calls and transcripts, centralizing business conversations. It helps teams analyze interactions and extract insights to improve customer experience.

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Introduction

This guide walks you through connecting Retellai to LlamaIndex using the Composio tool router. By the end, you'll have a working Retellai agent that can list all phone numbers linked to your account, retrieve call details for a specific agent this week, buy a new phone number with area code 415 through natural language commands.

This guide will help you understand how to give your LlamaIndex agent real control over a Retellai account through Composio's Retellai MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Retellai with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AICrewAI

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 Retellai
  • Connect LlamaIndex to the Retellai MCP server
  • Build a Retellai-powered agent using LlamaIndex
  • Interact with Retellai 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 Retellai MCP server, and what's possible with it?

The Retellai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Retellai account. It provides structured and secure access to your call records, phone numbers, and conversation transcripts, so your agent can perform actions like retrieving call details, managing phone numbers, initiating outbound calls, and analyzing voice data on your behalf.

  • Retrieve and analyze call records: Your agent can fetch detailed call logs, filter by agent or time, and surface insights from past conversations.
  • Initiate outbound and web-based calls: Easily direct your agent to start new phone or web calls between specific numbers or agents, supporting various business workflows.
  • Manage phone numbers and assignments: Buy, update, or delete phone numbers, and bind them to agents for streamlined inbound and outbound call handling.
  • Access and review call transcripts and details: Let your agent drill down into specific calls, pulling transcripts and metadata for compliance, training, or analytics.
  • Explore and configure voice settings: Fetch detailed information about available voice options, including provider, accent, gender, and preview audio for customization of call experiences.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step10 STEPS
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 Retellai account and project
  • Basic familiarity with async Python/Typescript
2

Getting API Keys for OpenAI, Composio, and Retellai

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID
3

Installing dependencies

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

Create a new Typescript project and install the necessary dependencies:

  • @composio/llamaindex: Composio's LlamaIndex integration
  • @llamaindex/openai: OpenAI LLM integration
  • @llamaindex/tools: MCP client for LlamaIndex
  • @llamaindex/workflow: Workflow framework for LlamaIndex
  • dotenv: Environment variable management
4

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

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 Retellai access
5

Import modules

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();

Create a new file called retellai_llamaindex_agent.ts and import the required modules:

Key imports:

  • dotenv.config loads .env at runtime
  • readline gives us a simple CLI chat loop
  • Composio is the main Composio SDK client
  • mcp connects to an MCP endpoint
  • createAgent builds a LlamaIndex agent
  • openai configures the LLM backend
6

Load environment variables and initialize Composio

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");

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

7

Create a Tool Router session and build the agent function

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: ["retellai"],
    },
  );

  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 Retellai actions." ,
    llm,
    tools,
  });

  return agent;
}

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, retellai)
  • 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 Retellai tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
8

Create an interactive chat loop

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();
}

What's happening:

  • We're creating a direct terminal interface to chat with Retellai
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • The agent processes the request, selects appropriate Retellai tools, and returns a result
  • We extract the answer from the result data structure and display it to the user
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are streamed in a clear, readable format
9

Define the main entry point

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

main();

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 Retellai
10

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Retellai, then start asking questions.

Complete Code

Here's the complete code to get you started with Retellai and LlamaIndex:

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: ["retellai"],
    },
  );

  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 Retellai 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 Retellai to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Retellai 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.
TOOLS

Supported Tools

Every Retellai action and event your agent gets out of the box.

Add community voice

Add a community voice from ElevenLabs to your Retell voice library.

Add sources to knowledge base

Tool to add sources (documents, URLs, text) to an existing knowledge base in Retell AI.

Buy a new phone number bind agents

This endpoint allows purchasing a new phone number with a specified area code and binding it to designated agents for inbound and outbound calls.

Create Voice AI Agent

Create a new voice AI agent with specified configuration.

Create a new outbound phone call

Initiate an outbound call by POST to '/v2/create-phone-call'.

Create a new web call

The /v2/create-web-call endpoint creates a web call with a unique agent ID, returning call details like type, token, call ID, and status in JSON format, with a 201 response.

Create Batch Test

Tool to create a batch test job that runs multiple test cases against an agent.

Create a new chat session

Tool to create a new chat session with a chat agent.

Create a new chat agent

Create a new chat agent with specified configuration.

Create chat completion

Tool to create a chat completion for an existing chat session, generating the agent's response to a user message.

Create conversation flow

Create a new Conversation Flow that can be attached to an agent for response generation.

Create conversation flow component

Creates a new shared conversation flow component at POST '/create-conversation-flow-component'.

Create a new knowledge base

Tool to create a new knowledge base in Retell AI with texts, files, and URLs.

Create Retell LLM Response Engine

Create a new Retell LLM Response Engine that can be attached to an agent.

Create Test Case Definition

Tool to create a test case definition for agent QA testing in Retell AI.

Delete agent

Deletes an existing agent by its unique identifier.

Delete call

Delete a specific call and its associated data by call ID.

Delete chat agent

Delete an existing chat agent by its unique identifier.

Delete conversation flow

Delete a conversation flow and all its versions.

Delete conversation flow component

Delete a shared conversation flow component.

Delete knowledge base

Delete an existing knowledge base by its unique identifier.

Delete knowledge base source

Delete an existing source from a knowledge base.

Delete phone number

Tool to delete an existing phone number from Retell AI.

Delete Retell LLM

Delete an existing Retell LLM Response Engine by its unique identifier.

Delete test case definition

Delete a test case definition by its unique identifier.

End chat

Tool to end an active chat session.

Retrieve details of a specific agent

Retrieve details of a specific agent by its unique identifier.

Get agent versions

Tool to retrieve all versions of a specific agent.

Get batch test

Retrieve details and results of a specific batch test job.

Get chat details

Tool to retrieve details of a specific chat session by chat ID.

Retrieve details of a specific chat agent

Retrieve details of a specific chat agent by its unique identifier.

Get all versions of a chat agent

Retrieve all versions of a specific chat agent by its unique identifier.

Get concurrency

Retrieves the current concurrency and concurrency limits for the organization.

Get Conversation Flow

Retrieve details of a specific Conversation Flow by its ID.

Get conversation flow component

Retrieves a shared conversation flow component by its unique identifier.

Get knowledge base

Retrieve details of a specific knowledge base by its unique identifier.

Retrieve details of a specific Retell LLM

Retrieve details of a specific Retell LLM Response Engine by its unique identifier.

Import phone number

Tool to import a phone number from custom telephony and bind agents to it.

List agents

Retrieves a list of all agents associated with the account.

List all chats

Tool to retrieve a list of all chats associated with the account.

List all phone numbers

Retrieves a list of all phone numbers associated with the account.

List batch tests

Tool to list batch test jobs for a response engine.

List chat agents

Tool to retrieve a list of all chat agents associated with the account.

List conversation flow components

Retrieves a list of all shared conversation flow components.

List conversation flows

Tool to list all conversation flows that can be attached to an agent.

List knowledge bases

Tool to retrieve all knowledge bases associated with the account.

List Retell LLMs

Tool to list all Retell LLM Response Engines that can be attached to an agent.

List test case definitions

Tool to list test case definitions for a response engine (Retell LLM or Conversation Flow).

List test runs

Tool to list all test case jobs (test runs) for a batch test job.

List voices

List all voices available to the user.

Publish agent

Publishes the latest version of the agent and creates a new draft agent with a newer version.

Publish chat agent

Publishes the latest version of the chat agent and creates a new draft chat agent with a newer version.

Register phone call

Register a phone call for custom telephony integration with Retell AI.

Retrieve call details

Tool to retrieve call details with filtering options.

Retrieve call details by id

Retrieve call details by ID for web/phone calls, including type, agent ID, status, timestamps, and web access token; covering responses from success to server errors.

Retrieve phone number details

Tool to retrieve details of a specific phone number from Retell AI.

Retrieve details of a specific voice

Tool to retrieve details of a specific voice by its voice_id.

Search community voice

Search for community voices from voice providers.

Update agent

Update an existing agent's latest draft version.

Update call

Update an active call's parameters such as metadata, dynamic variables, or data storage settings.

Update chat agent

Update an existing chat agent configuration.

Update chat metadata

Tool to update metadata and sensitive data storage settings for an existing chat.

Update conversation flow

Update an existing conversation flow configuration.

Update conversation flow component

Update an existing shared conversation flow component by its ID.

Update phone number configuration

Update agent bound to a purchased phone number.

Update Retell LLM Response Engine

Update an existing Retell LLM Response Engine by its unique identifier.

Update test case definition

Update a test case definition for agent testing.

FRAMEWORKS

How to build Retellai MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Retellai MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Retellai MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Retellai MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Retellai MCP with Claude Cowork

Codex logo

Codex

Use Retellai MCP with Codex

OpenClaw logo

OpenClaw

Use Retellai MCP with OpenClaw

Hermes logo

Hermes

Use Retellai MCP with Hermes

CLI logo

CLI

Use Retellai MCP with CLI

Google ADK logo

Google ADK

Use Retellai MCP with Google ADK

LangChain logo

LangChain

Use Retellai MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Retellai MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Retellai MCP with Mastra AI

CrewAI logo

CrewAI

Use Retellai MCP with CrewAI

FAQ

Frequently asked questions

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

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 Retellai tools.

Yes, absolutely. You can configure which Retellai 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.

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 Retellai data and credentials are handled as safely as possible.

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