ai.smithery/kirbah-mcp-youtube

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# YouTube Data MCP Server (@kirbah/mcp-youtube)

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**A production-grade YouTube Data MCP server engineered specifically for AI agents.**

Unlike standard API wrappers that flood your LLM with redundant data, this server strips away YouTube's heavy payload bloat. It is designed to save you massive amounts of context window tokens, protect your daily API quotas via caching, and run reliably without breaking your workflows.

## Why Choose This Server?

Most MCP servers are weekend projects. `@kirbah/mcp-youtube` is built for reliable, daily, cost-effective agentic workflows.

### 📉 1. Save Up to 87% on Tokens (and Context Window)

The raw YouTube API returns massive JSON payloads filled with nested eTags, redundant thumbnails, and localization data that LLMs don't need. This server structures the data to give your LLM exactly what it needs to reason, and nothing else.

```mermaid
%%{init: { "theme": "base", "themeVariables": { "xyChart": { "plotColorPalette": "#ef4444, #22c55e" } } } }%%
xychart-beta
    title "Token Consumption (Lower is Better)"
    x-axis ["getVideoDetails", "searchVideos", "getChannelStats"]
    y-axis "Context Tokens" 0 --> 1200
    bar "Raw YouTube API" [854, 1115, 673]
    bar "MCP-YouTube (Optimized)" [209, 402, 86]
```

| API Method             | Raw YouTube Tokens | MCP-YouTube Tokens | Token Savings | Data Size       |
| :--------------------- | :----------------- | :----------------- | :------------ | :-------------- |
| `getChannelStatistics` | 673                | **86**             | **~87% Less** | 1.9 KB ➔ 0.2 KB |
| `getVideoDetails`      | 854                | **209**            | **~75% Less** | 2.9 KB ➔ 0.6 KB |
| `searchVideos`         | 1115               | **402**            | **~64% Less** | 3.4 KB ➔ 1.2 KB |

_(Curious? You can compare the [raw API responses vs optimized outputs](examples/comparisons/) in the examples folder)._

### 🛡️ 2. Protect Your API Quotas (Smart Caching)

The YouTube Data API has strict daily limits (10,000 quota units). If your LLM gets stuck in a loop or re-asks a question, standard servers will drain your API limit in minutes.
This server includes an optional **MongoDB caching layer**. If your agent requests a video details or searches the same trending videos twice, the server serves it from the cache - costing you **0 API quota points**.

### 🏗️ 3. Production-Grade & Actively Maintained

Tired of MCP tools crashing your AI client? This server is built to be a rock-solid dependency:

- **97% Test Coverage:** Comprehensively unit-tested (check the Codecov badge).
- **Zero Lint Errors/Warnings:** Enforces strict, clean code (`npm run lint` passes 100%).
- **Active Security:** Automated Dependabot patching ensures underlying libraries are never left with known vulnerabilities.
- **Strict Type Safety:** Built using Zod validation and the robust MCP TypeScript Starter architecture.

---

## Quick Start: Installation

### 🟢 Zero-Config Mode (No API Key Required)

**Want to just fetch transcripts?** You can use this server immediately without any configuration! Just install and go. Add a YouTube API key later to unlock deep search and analytics.

The easiest way to install this server is by clicking the **"Add to Claude Desktop"** button on the [Glama server page](https://glama.ai/mcp/servers/@kirbah/mcp-youtube).

If you are configuring manually (e.g., in Cursor), just add this bare-minimum setup:

```json
{
  "mcpServers": {
    "youtube": {
      "command": "npx",
      "args": ["-y", "@kirbah/mcp-youtube"]
    }
  }
}
```

_✨ **Tip:** In Zero-Config mode, you can ask your AI to simply "Read the transcript for `youtube://transcript/{videoId}`"!_

### 🟡 Manual Configuration (Unlock All Features)

If you prefer to configure your MCP client manually (e.g., Claude Desktop or Cursor), add the