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M MCP Servers Developer low

Klavis-AI/YouTube

by Various

Klavis AI: MCP integration platforms that let AI agents use tools reliably at any scale

MCP

Klavis-AI/YouTube

Added 1 June 2026

#agents #ai #ai-agents #api #developer-tools #discord #function-calling #integration

Overview

Klavis-AI/YouTube is a Model Context Protocol (MCP) server that exposes YouTube data endpoints for AI agents. It allows agents to perform searches, retrieve video metadata, and access channel information through a standardized tool interface. Built in Python, it is part of the Klavis AI ecosystem designed for reliable tool integration at scale.

Best for

Best for
Developers building AI agents that need structured, programmatic access to YouTube data

Use cases

  • Enabling an AI assistant to search YouTube and return video results to users
  • Feeding YouTube video captions or metadata into a downstream analysis pipeline
  • Building agent workflows that retrieve channel details or playlists automatically

Notes

Klavis-AI/YouTube is a Model Context Protocol (MCP) server that exposes YouTube data endpoints for AI agents. It allows agents to perform searches, retrieve video metadata, and access channel information through a standardized tool interface. Built in Python, it is part of the Klavis AI ecosystem designed for reliable tool integration at scale.

5,749 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.

Use cases

  • Enabling an AI assistant to search YouTube and return video results to users
  • Feeding YouTube video captions or metadata into a downstream analysis pipeline
  • Building agent workflows that retrieve channel details or playlists automatically

Pros

  • Well‑starred open‑source project with community traction
  • Integrates seamlessly with MCP‑compatible AI agent frameworks
  • Part of a larger platform that scales tool usage reliably

Cons

  • Requires understanding of the MCP protocol to set up and use effectively
  • May not cover every YouTube API endpoint or advanced features
  • Dependency on the Klavis platform’s stability and continued development

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Well‑starred open‑source project with community traction
  • Integrates seamlessly with MCP‑compatible AI agent frameworks
  • Part of a larger platform that scales tool usage reliably

Cons

  • Requires understanding of the MCP protocol to set up and use effectively
  • May not cover every YouTube API endpoint or advanced features
  • Dependency on the Klavis platform’s stability and continued development

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