How to integrate Bolna MCP with Mastra AI

Trusted by
AWS
Glean
Zoom
Airtable

30 min · no commitment · see it on your stack

Bolna logo
Mastra AI logo
divider

Introduction

This guide walks you through connecting Bolna to Mastra AI using the Composio tool router. By the end, you'll have a working Bolna agent that can list all voice agents available to me, initiate a call using your sales agent, get status of recent agent executions through natural language commands.

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

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

Also integrate Bolna with

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 Bolna tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Bolna 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 Bolna 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 Bolna MCP server, and what's possible with it?

The Bolna MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bolna account. It provides structured and secure access to your Bolna voice agent platform, so your agent can perform actions like listing agents, making phone calls, managing executions, and retrieving analytics on your behalf.

  • Automated voice call initiation: Let your AI agent instantly initiate phone calls using your Bolna conversational agents, streamlining outreach and support tasks.
  • Agent and phone number management: Effortlessly fetch and list all your Bolna agents or phone numbers, making it easy to review and organize your voice assets.
  • Real-time execution monitoring: Retrieve detailed information about specific call executions or monitor all executions for a given agent to track performance and outcomes.
  • Batch processing for agents: List and manage batch operations associated with your agents, supporting bulk workflows and campaign management.
  • Agent cleanup and maintenance: Quickly delete agents or batches that are no longer needed, keeping your Bolna environment organized and up to date.

Supported Tools & Triggers

Tools
Add Provider to BolnaTool to add a new telephony or voice service provider to your Bolna account.
Copy Bolna AgentTool to create a duplicate copy of an existing Bolna voice AI agent.
Create Bolna Voice AI Agent (v2)Tool to create a new Bolna Voice AI agent using the v2 API.
Create Bolna BatchTool to create a new outbound calling batch by uploading a CSV of contacts to obtain a batch_id.
Create Bolna KnowledgebaseTool to create a new knowledgebase for Voice AI agents to reference during conversations.
Create Template AgentTool to create a new Bolna Voice AI agent from a template.
Delete agent by idPermanently delete a Voice AI agent and all associated data including batches, executions, and configurations
Delete batch by idPermanently delete a batch campaign by its ID, removing it from the system.
Delete KnowledgebaseTool to permanently delete a knowledgebase from your Bolna account.
Fetch all batches by agent idRetrieve all batches associated with a specific Bolna Voice AI agent.
Get all agentsRetrieve all agents configured in your Bolna account Returns a comprehensive list of all voice agents with their configurations including: - Agent metadata (ID, name, type, status) - Task configurations (conversation settings, toolchains) - AI model settings (LLM, transcriber, synthesizer) - Webhook and phone number assignments - System prompts and guardrails This is useful for listing available agents, checking agent configurations, or finding specific agents by their properties.
Get execution by idRetrieve detailed information about a specific phone call execution by its ID.
Get knowledgebase by IDTool to retrieve details of a specific knowledgebase by its ID.
Get User InformationTool to retrieve information about the authenticated user.
Import Bolna AgentTool to import an existing Bolna voice AI agent by its ID.
List agents (paginated)Tool to retrieve a paginated list of all agents in your Bolna account.
List KnowledgebasesTool to retrieve all knowledgebases from your Bolna account.
List all phone numbersTool to list all phone numbers associated with your Bolna account.
List all providersRetrieve all providers associated with your Bolna account Returns a list of all configured providers including: - Provider IDs (unique identifiers) - Provider names (e.
List available voicesTool to list all available voices that can be utilized for Voice AI agents.
Make an outbound phone call from agentInitiate an outbound phone call using a configured Bolna Voice AI agent.
Remove Provider from Bolna AccountTool to remove a provider from your Bolna account by its key name.
Retrieve agent by idRetrieve complete configuration and details for a specific Bolna voice AI agent by its ID.
Retrieve agent execution detailsRetrieve detailed information about a specific execution (call/conversation) by an agent, including transcript, costs, duration, status, and telephony data
Retrieve agent execution statusRetrieve all executions for a specific agent with pagination and filtering support.
Retrieve Batch Details by IDRetrieve comprehensive details about a specific Bolna batch by its ID.
Retrieve batch execution listRetrieve all executions from a specific batch with pagination support.
Schedule Batch by IDSchedule a batch to execute at a specific time.
Search available phone numbersTool to search for available phone numbers that can be purchased for Bolna Voice agents.
Setup inbound call for agentAdd agent for inbound calls
Stop Agent CallsTool to stop all queued or scheduled calls for a specific Voice AI agent.
Stop batch by idStop a running batch by its ID.
Update Bolna Voice AI Agent (v2)Tool to update all settings and configuration of an existing Bolna Voice AI agent using the v2 API.

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:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

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 Bolna through MCP.

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

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

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

Create a Tool Router session for Bolna

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

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

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 Bolna toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "bolna-mastra-agent",
    instructions: "You are an AI agent with Bolna 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

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: {
        bolna: 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 Bolna 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 Bolna 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: ["bolna"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "bolna-mastra-agent",
    instructions: "You are an AI agent with Bolna 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: { bolna: 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 Bolna 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

How to build Bolna MCP Agent with another framework

FAQ

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

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

Can I use Tool Router MCP with Mastra AI?

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 Bolna tools.

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

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

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.