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How to integrate Vapi MCP with Mastra AI

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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.

38 Tools

Introduction

This guide walks you through connecting Vapi to Mastra AI using the Composio tool router. By the end, you'll have a working Vapi agent that can create and update voice assistants, list calls and chats, manage phone numbers, run evals, and query analytics through natural language commands.

This guide will help you understand how to give your Mastra AI 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

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TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Vapi tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Vapi tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Vapi agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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 to your voice assistants, calls, chats, phone numbers, and analytics, so your agent can create assistants, review conversations, analyze performance, manage phone numbers, and configure monitoring on your behalf.

  • Voice assistant configuration: Have your agent create new voice assistants with selected transcribers, voices, and AI models, or update existing assistant settings.
  • Call and chat review: Let the agent list calls and chats, then retrieve the details needed to examine specific conversations.
  • Analytics and quality evaluation: Direct your agent to run analytics queries, review evaluations, and remove evaluations you no longer need.
  • Phone number management: Instruct your agent to list, update, or delete phone numbers connected to your Vapi organization.
  • Monitoring and supporting resources: Have your agent create and review monitoring policies, retrieve stored files, inspect available tools and provider resources, or create new sessions.

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Vapi through MCP.
3

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_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 your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models
5

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session
6

Create a Tool Router session for Vapi

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["vapi"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Vapi MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "vapi" for Vapi access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Vapi toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "vapi-mastra-agent",
    instructions: "You are an AI agent with Vapi tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM
9

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

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

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        vapi: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Vapi toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

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

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["vapi"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      vapi: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "vapi-mastra-agent",
    instructions: "You are an AI agent with Vapi tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { vapi: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Vapi through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows
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

Fetch chat details by ID, including available messages, costs, and assistant configuration.

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

Create an OpenAI-compatible chat with a Vapi assistant or squad and receive a JSON response.

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

Delete a Vapi call by its unique identifier.

Delete Eval

Tool to delete an eval by ID.

Delete Phone Number

Delete a phone number from your Vapi organization by ID.

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

Fetch selected call details by ID, including available status, cost, messages, and transcript information.

Get File

Tool to retrieve a file by its ID from Vapi.

List Monitoring Policies

Tool to retrieve monitoring policies 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 Phone Numbers

Tool to list phone numbers in the Vapi organization.

List Provider Resources

List Vapi provider pronunciation dictionaries for 11Labs or Cartesia, with optional ID and timestamp filters and pagination.

Update Insight

Update an existing Vapi insight configuration, including its name, queries, time range, or visualization settings.

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.

Get Tool

Fetch a Vapi tool by ID and return selected configuration details, including type, messages, function definition, and server settings.

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

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Codex

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OpenClaw logo

OpenClaw

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Hermes

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Google ADK logo

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Vercel AI SDK

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LlamaIndex

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CrewAI logo

CrewAI

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Pydantic AI logo

Pydantic AI

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AutoGen logo

AutoGen

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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. Mastra AI 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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