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YouTube MCP Tools for AI Agents

Let an agent search YouTube and retrieve video details for research, recommendations, and content workflows.

Available Tools

2 tools available in this integration

Youtube.GetYoutubeVideoDetails

Get details about a YouTube video.

Youtube.SearchForVideos

Search for YouTube videos related to the query.

Why agent-optimized tools matter

Built for intent, not API schemas

Ask the agent to "find three clear videos explaining this topic and return their links." Arcade helps it use the right YouTube tools without guessing search inputs or video IDs.

Up to 100x fewer tokens

YouTube searches return focused matches, and the agent can fetch fuller details only for videos worth inspecting. That keeps a research pass from loading unnecessary metadata for every result.

Complete the workflow end to end

Search a topic, compare matching videos, inspect the strongest candidates, and return a ranked shortlist through one toolkit designed around the complete video-discovery task.

Make actions predictable and controlled

Arcade tools return structured results and useful errors across users and runs. Teams can apply scope restrictions, redaction, and approval policies so agents follow the same controls every time.

Securing YouTube

The more capabilities agents get, the more useful they are. However, more capabilities bring more risks of undesired effects such as data loss and exfiltration.

This is why Arcade provides you with contextual rules that dictate how and when a tool is allowed to run. Arcade’s contextual access lets you govern tool visibility and behavior at every stage of execution and control who can see a tool, what inputs are allowed, and what comes back.

Learn about Contextual Access Policies

For YouTube, you can implement some of these policies:

Access when tools are listed for a user
  • Decide which tools an agent is allowed to see at all. A tool that is never listed cannot be called, whoever is asking.
Pre-execution before each tool call
  • Inspect the inputs a call is about to run with, and block it or send it for human approval when they fall outside what the agent should do unsupervised.
Post-execution after the tool returns
  • Redact email addresses, phone numbers, and external contact links from Youtube.GetYoutubeVideoDetails results before the model sees video descriptions.
  • Strip email addresses and phone numbers from descriptions returned by Youtube.SearchForVideos so an agent cannot extract personal contact details from search results.

How to use YouTube with your agent

Pick your MCP client below and follow the setup from authentication to your first YouTube search. Then try the example prompts with your agent.

Your questions, answered

A YouTube MCP server exposes YouTube capabilities as structured tools that an AI agent can call through the Model Context Protocol. With Arcade, an agent can search for videos and retrieve details about specific videos.

YouTube's API provides the underlying video search and metadata access; Arcade provides the MCP server and runtime around it. That runtime handles the shared credential, approval and redaction policies, and access from supported frameworks and clients.

Arcade agents can search for videos related to a query and retrieve details about a specific YouTube video. They cannot upload, edit, delete, comment on, or manage YouTube accounts through this toolkit.

This toolkit uses a shared API key or secret configured once, rather than asking each user to authorize a YouTube account. The credential must have access to the YouTube API operations used by video search and detail lookups.

No. This toolkit uses one shared API key or secret configured for the integration, so users do not connect individual YouTube accounts. Arcade brokers the credential instead of passing it to the model.

Yes. Contextual Access policies can require human approval before a call, although the available YouTube actions are read-only and do not publish, edit, or delete content. A policy can also redact fields from returned video data or hide the toolkit from an agent.

Arcade proxies YouTube API calls and does not persist YouTube content as part of normal tool execution. The shared credential is brokered and stored encrypted at rest, and the model never receives it.

Any framework or client that can connect to Arcade's MCP gateway or tool APIs works, including LangChain, OpenAI Agents, CrewAI, Claude Desktop, Claude Code, Cursor, Visual Studio Code, Microsoft Copilot Studio, and GitHub Copilot.

Arcade continues using the configured credential while it remains valid. If the API key or secret is revoked, rotated, or no longer accepted, calls stop until the credential is updated and reconnected.

YouTube API quotas and rate limits apply to calls made through Arcade. The available information does not specify a separate Arcade quota or a per-call result limit, so plan for the limits attached to the configured YouTube API credential.

Ready to actually ship your agent?

Connect your agent to YouTube with a shared API key, agent-optimized tools and approval controls for consequential actions.

Build Your Agent Read the YouTube Quickstart