How to integrate Vapi MCP with CrewAI

This guide walks you through connecting Vapi to CrewAI using the Composio tool router. By the end, you'll have a working Vapi agent that can start a new outbound call campaign, get transcript from the last agent call, pause all ongoing voice agent sessions through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Vapi account through Composio's Vapi MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Vapi is a voice AI platform for building, testing, and deploying conversational voice agents. It provides real-time responses and seamless integration for voice-driven applications.

42 Tools

Introduction

This guide walks you through connecting Vapi to CrewAI using the Composio tool router. By the end, you'll have a working Vapi agent that can start a new outbound call campaign, get transcript from the last agent call, pause all ongoing voice agent sessions through natural language commands.

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

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

Also integrate Vapi with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Vapi connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Vapi
  • Build a conversational loop where your agent can execute Vapi operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Vapi MCP server, and what's possible with it?

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

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 step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Vapi connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
2

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
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Vapi via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

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")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Vapi MCP URL
6

Create a Composio Tool Router session for Vapi

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["vapi"])

url = session.mcp.url
What's happening:
  • You create a Vapi only session through Composio
  • Composio returns an MCP HTTP URL that exposes Vapi tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Vapi and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_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.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["vapi"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Vapi through Composio's Tool Router. The agent can perform Vapi operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
TOOLS

Supported Tools

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

Update Assistant

Tool to update an existing Vapi assistant configuration.

List Calls

Tool to list calls from Vapi.

Delete Chat

Tool to delete a chat by its ID from Vapi.

Get Chat

Tool to fetch chat details by ID.

Create Analytics Queries

Tool to create and execute analytics queries on VAPI data.

Create Assistant

Tool to create a new Vapi assistant with specified transcriber, voice, and AI model configurations.

Create Eval

Tool to create an eval for testing conversation flows.

Create OpenAI Chat

Tool to create an OpenAI-compatible chat using the Vapi API.

Create Phone Number

Tool to create a phone number with Vapi.

Create Monitoring Policy

Tool to create a monitoring policy in VAPI.

Create Provider Resource

Tool to create an 11Labs pronunciation dictionary resource.

Create Scorecard

Tool to create a scorecard for observability and evaluation.

Delete Call

Tool to delete a call by its unique identifier.

Delete Eval

Tool to delete an eval by ID.

Delete Phone Number

Tool to delete a phone number from Vapi.

Get Eval

Tool to retrieve an eval by its ID.

Delete Eval Run

Tool to delete an eval run by its ID from Vapi.

Update Eval

Tool to update an existing eval in Vapi.

Get Assistant

Tool to retrieve a specific assistant by ID from Vapi.

Get Call

Tool to fetch call details by ID.

Get File

Tool to retrieve a file by its ID from Vapi.

Get Insights

Tool to retrieve insights from Vapi.

List Monitoring Policies

Tool to retrieve monitoring policies from Vapi.

Get Observability Scorecard

Tool to list observability scorecards with optional filtering and pagination.

List Provider Resources

Tool to list provider resources from Vapi.

List Structured Outputs

Tool to list structured outputs with optional filtering.

Get Insights

Tool to retrieve insights from VAPI.

List Assistants

Tool to list all assistants in your VAPI organization.

List Chats

Tool to retrieve a list of chat conversations from VAPI.

List Evals

Tool to retrieve a paginated list of evals from Vapi.

List Provider Resources

Tool to retrieve provider resources from Vapi (e.

Update Insight

Tool to update an existing insight configuration in VAPI.

Create Phone Number

Tool to create a phone number with VAPI.

List Scorecards

Tool to retrieve a paginated list of scorecards from Vapi.

Create Session

Tool to create a new session in Vapi.

List Sessions

Tool to retrieve a paginated list of sessions from VAPI.

List Structured Outputs

Tool to list structured outputs with optional filtering and pagination.

Get Tool

Tool to fetch tool details by ID.

Test Code Tool Execution

Tool to test TypeScript code execution in Vapi's code tool environment.

Update Tool

Tool to update an existing Vapi tool configuration.

Update Phone Number

Tool to update an existing phone number configuration in VAPI.

Upload File

Tool to upload a file to Vapi Knowledge Base.

FRAMEWORKS

How to build Vapi MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Vapi MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Vapi MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Vapi MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Vapi MCP with Claude Cowork

Codex logo

Codex

Use Vapi MCP with Codex

OpenClaw logo

OpenClaw

Use Vapi MCP with OpenClaw

Hermes logo

Hermes

Use Vapi MCP with Hermes

CLI logo

CLI

Use Vapi MCP with CLI

Google ADK logo

Google ADK

Use Vapi MCP with Google ADK

LangChain logo

LangChain

Use Vapi MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Vapi MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Vapi MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Vapi MCP with LlamaIndex

FAQ

Frequently asked questions

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

Yes, you can. CrewAI 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 Vapi tools.

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

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