How to integrate Youtube MCP with Mastra AI

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Introduction

This guide walks you through connecting Youtube to Mastra AI using the Composio tool router. By the end, you'll have a working Youtube agent that can list your most recent uploaded videos, get subscriber count for your channel, search youtube for trending tutorials through natural language commands.

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

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

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

The Youtube MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Youtube account. It provides structured and secure access to your channel data, so your agent can perform actions like searching videos, managing playlists, retrieving channel insights, and handling subscriptions on your behalf.

  • Channel activity monitoring: Let your agent fetch and summarize recent channel activities, including uploads, likes, playlist additions, and more, to keep you up to date at a glance.
  • Automated video and playlist management: Easily list videos from any channel, retrieve your own playlists, and organize your content—all through AI-driven commands.
  • Channel analytics and statistics: Ask your agent to pull detailed channel metrics such as subscriber counts, total views, or video counts for quick reporting and insights.
  • Subscription management: Have your agent list your current subscriptions or even subscribe you to new channels based on your interests or instructions.
  • Search and caption handling: Empower your agent to search YouTube for videos, channels, or playlists, as well as retrieve and download caption tracks for accessible viewing and content repurposing.

Supported Tools & Triggers

Tools
Triggers
Add Video to PlaylistTool to add a video to a playlist by inserting a playlist item.
Insert Channel SectionTool to create a new channel section for the authenticated user's YouTube channel.
Insert Comment ReplyTool to create a reply to an existing YouTube comment.
Create PlaylistTool to create a new YouTube playlist on the authenticated user's channel.
Delete Channel SectionTool to delete a YouTube channel section.
Delete CommentTool to delete a YouTube comment owned by the authenticated user or channel.
Delete PlaylistTool to delete a YouTube playlist owned by the authenticated user/channel.
Delete Playlist ItemTool to delete a playlist item (remove a video from a playlist).
Delete VideoTool to delete a YouTube video owned by the authenticated user/channel.
Get Channel ActivitiesGets recent activities from a YouTube channel including video uploads, playlist additions, likes, and other channel events.
Get channel ID by handleRetrieves the YouTube Channel ID for a specific YouTube channel handle.
Get Channel StatisticsGets detailed statistics for YouTube channels including subscriber counts, view counts, and video counts.
Video Details BatchRetrieves multiple YouTube video resource parts in a single batch call.
Get Video RatingRetrieves the ratings that the authorized user gave to a list of specified videos.
List captionsRetrieves a list of caption tracks for a YouTube video.
List Channel SectionsTool to retrieve channel sections from YouTube.
List channel videosLists videos from a specified YouTube channel.
List CommentsList individual comments from YouTube videos.
List Comment ThreadsTool to retrieve comment threads from YouTube videos or channels matching API request parameters.
List I18n LanguagesReturns a list of application languages that the YouTube website supports.
List I18n RegionsTool to retrieve a list of content regions that the YouTube website supports.
List Live Chat MessagesTool to list live chat messages for a specific chat.
List Playlist ImagesTool to retrieve playlist images associated with a specific playlist.
List Playlist ItemsTool to list videos in a playlist, with pagination support.
List Super Chat EventsLists Super Chat events for a channel, showing supporter purchases during live streams.
List user playlistsRetrieves playlists owned by the authenticated user, implicitly using mine=True.
List user subscriptionsRetrieves the authenticated user's YouTube channel subscriptions, allowing specification of response parts and pagination.
List Video Abuse Report ReasonsTool to retrieve a list of abuse report reasons that can be used to report abusive videos on YouTube.
List Video CategoriesTool to list YouTube video categories that can be associated with videos.
Download YouTube caption trackDownloads a specific YouTube caption track, which must be owned by the authenticated user, and returns its content as text.
Multipart upload videoUploads a video to YouTube using multipart upload in a single request.
Post Comment on VideoTool to post a new top-level comment on a YouTube video.
Rate VideoTool to add a like or dislike rating to a YouTube video, or remove an existing rating.
Report Video for AbuseTool to report a YouTube video for containing abusive content.
Search YouTubeSearches YouTube for videos, channels, or playlists using a query term, returning the raw API response.
Set Comment Moderation StatusTool to set the moderation status of one or more YouTube comments.
Subscribe to channelSubscribes the authenticated user to a specified YouTube channel, identified by its unique `channelId` which must be valid and existing.
Unsubscribe from channelTool to unsubscribe the authenticated user from a YouTube channel by deleting a subscription.
Update caption trackUpdates a YouTube caption track's metadata such as name, language, or draft status.
Update channelUpdates a channel's metadata including branding settings and localizations.
Update Channel SectionTool to update an existing YouTube channel section by ID.
Update CommentTool to modify the text of an existing YouTube comment.
Update PlaylistTool to modify an existing YouTube playlist's metadata (title, description, privacy status).
Update Playlist ItemTool to modify a playlist item's properties such as position or note.
Update thumbnailSets the custom thumbnail for a YouTube video using an image from a URL.
Update videoUpdates metadata for a YouTube video identified by videoId, which must exist; an empty list for tags removes all existing tags.
Upload videoUploads a video from a local file path to a YouTube channel; the video file must be in a YouTube-supported format.

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 Youtube 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 Youtube

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

  const composioMCPUrl = session.mcp.url;
  console.log("Youtube MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "youtube" for Youtube 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 Youtube toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "youtube-mastra-agent",
    instructions: "You are an AI agent with Youtube 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: {
        youtube: 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 Youtube 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 Youtube 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: ["youtube"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "youtube-mastra-agent",
    instructions: "You are an AI agent with Youtube 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: { youtube: 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 Youtube 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 Youtube MCP Agent with another framework

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OpenCode

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VS Code logo

VS Code

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FAQ

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

With a standalone Youtube MCP server, the agents and LLMs can only access a fixed set of Youtube tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Youtube 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 Youtube tools.

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

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

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