How to integrate Retellai MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Retellai to the OpenAI Agents SDK 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 OpenAI Agents SDK 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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Retellai
  • Configure an AI agent that can use Retellai as a tool
  • Run a live chat session where you can ask the agent to perform Retellai operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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.

Supported Tools & Triggers

Tools
Add community voiceAdd a community voice from ElevenLabs to your Retell voice library.
Add sources to knowledge baseTool to add sources (documents, URLs, text) to an existing knowledge base in Retell AI.
Buy a new phone number bind agentsThis 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 AgentCreate a new voice AI agent with specified configuration.
Create a new outbound phone callInitiate an outbound call by POST to '/v2/create-phone-call'.
Create a new web callThe /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 TestTool to create a batch test job that runs multiple test cases against an agent.
Create a new chat sessionTool to create a new chat session with a chat agent.
Create a new chat agentCreate a new chat agent with specified configuration.
Create chat completionTool to create a chat completion for an existing chat session, generating the agent's response to a user message.
Create conversation flowCreate a new Conversation Flow that can be attached to an agent for response generation.
Create conversation flow componentCreates a new shared conversation flow component at POST '/create-conversation-flow-component'.
Create a new knowledge baseTool to create a new knowledge base in Retell AI with texts, files, and URLs.
Create Retell LLM Response EngineCreate a new Retell LLM Response Engine that can be attached to an agent.
Create Test Case DefinitionTool to create a test case definition for agent QA testing in Retell AI.
Delete agentDeletes an existing agent by its unique identifier.
Delete callDelete a specific call and its associated data by call ID.
Delete chat agentDelete an existing chat agent by its unique identifier.
Delete conversation flowDelete a conversation flow and all its versions.
Delete conversation flow componentDelete a shared conversation flow component.
Delete knowledge baseDelete an existing knowledge base by its unique identifier.
Delete knowledge base sourceDelete an existing source from a knowledge base.
Delete phone numberTool to delete an existing phone number from Retell AI.
Delete Retell LLMDelete an existing Retell LLM Response Engine by its unique identifier.
Delete test case definitionDelete a test case definition by its unique identifier.
End chatTool to end an active chat session.
Retrieve details of a specific agentRetrieve details of a specific agent by its unique identifier.
Get agent versionsTool to retrieve all versions of a specific agent.
Get batch testRetrieve details and results of a specific batch test job.
Get chat detailsTool to retrieve details of a specific chat session by chat ID.
Retrieve details of a specific chat agentRetrieve details of a specific chat agent by its unique identifier.
Get all versions of a chat agentRetrieve all versions of a specific chat agent by its unique identifier.
Get concurrencyRetrieves the current concurrency and concurrency limits for the organization.
Get Conversation FlowRetrieve details of a specific Conversation Flow by its ID.
Get conversation flow componentRetrieves a shared conversation flow component by its unique identifier.
Get knowledge baseRetrieve details of a specific knowledge base by its unique identifier.
Retrieve details of a specific Retell LLMRetrieve details of a specific Retell LLM Response Engine by its unique identifier.
Import phone numberTool to import a phone number from custom telephony and bind agents to it.
List agentsRetrieves a list of all agents associated with the account.
List all chatsTool to retrieve a list of all chats associated with the account.
List all phone numbersRetrieves a list of all phone numbers associated with the account.
List batch testsTool to list batch test jobs for a response engine.
List chat agentsTool to retrieve a list of all chat agents associated with the account.
List conversation flow componentsRetrieves a list of all shared conversation flow components.
List conversation flowsTool to list all conversation flows that can be attached to an agent.
List knowledge basesTool to retrieve all knowledge bases associated with the account.
List Retell LLMsTool to list all Retell LLM Response Engines that can be attached to an agent.
List test case definitionsTool to list test case definitions for a response engine (Retell LLM or Conversation Flow).
List test runsTool to list all test case jobs (test runs) for a batch test job.
List voicesList all voices available to the user.
Publish agentPublishes the latest version of the agent and creates a new draft agent with a newer version.
Publish chat agentPublishes the latest version of the chat agent and creates a new draft chat agent with a newer version.
Register phone callRegister a phone call for custom telephony integration with Retell AI.
Retrieve call detailsTool to retrieve call details with filtering options.
Retrieve call details by idRetrieve 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 detailsTool to retrieve details of a specific phone number from Retell AI.
Retrieve details of a specific voiceTool to retrieve details of a specific voice by its voice_id.
Search community voiceSearch for community voices from voice providers.
Update agentUpdate an existing agent's latest draft version.
Update callUpdate an active call's parameters such as metadata, dynamic variables, or data storage settings.
Update chat agentUpdate an existing chat agent configuration.
Update chat metadataTool to update metadata and sensitive data storage settings for an existing chat.
Update conversation flowUpdate an existing conversation flow configuration.
Update conversation flow componentUpdate an existing shared conversation flow component by its ID.
Update phone number configurationUpdate agent bound to a purchased phone number.
Update Retell LLM Response EngineUpdate an existing Retell LLM Response Engine by its unique identifier.
Update test case definitionUpdate a test case definition for agent testing.

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

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Retellai project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Retellai.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Retellai Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["retellai"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only retellai.
  • The router checks the user's Retellai connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Retellai.
  • This approach keeps things lightweight and lets the agent request Retellai tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Retellai. "
        "Help users perform Retellai operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Retellai and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Retellai operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Retellai.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Retellai and OpenAI Agents SDK:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["retellai"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Retellai. "
        "Help users perform Retellai operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Retellai MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Retellai.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Retellai MCP Agent with another framework

FAQ

What are the differences in Tool Router MCP and Retellai MCP?

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.

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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.

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

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.

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 Retellai data and credentials are handled as safely as possible.

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