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YouTube Comments MCP Server

by 878787ya
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

yt_mcp — YouTube Comments MCP Server

一個遵循 Model Context Protocol (MCP) 的本機伺服器。提供工具：

  • fetch_comments(videoUrl, order="relevance|time", max=300) 以 YouTube Data API v3 取得並展開 頂層留言＋回覆，回傳 JSON 字串。

需求

  • Python 3.10+

  • 已啟用 YouTube Data API v3 的 API 金鑰

Related MCP server: mcp-server-youtube

安裝

uv venv
source .venv/bin/activate
uv pip install "mcp[cli]" httpx python-dotenv

設定金鑰（擇一）

A. 用 .env（推薦）

在專案根目錄建立 .env：

YOUTUBE_API_KEY=YOUR_API_KEY_HERE

B. 寫在客戶端設定的 env（見下方範例）

在 Claude Desktop 使用（本機 STDIO）

  1. 開啟：Settings → Developer → Local MCP servers → Edit Config

  2. 加入（請把絕對路徑換成你的實際路徑）：

{
  "mcpServers": {
    "yt_comments": {
      "command": "<abs path>/yt_mcp/.venv/bin/python",
      "args": ["<abs path>/yt_mcp/server.py"],
      "env": { "YOUTUBE_API_KEY": "YOUR_API_KEY" }  // 若已用 .env，可移除此段
    }
  }
}

也可不填 env，改用專案根目錄的 .env。

  1. 回到 Local MCP servers 啟動 yt_comments。

  2. 新開對話請 Claude 呼叫：

yt_comments.fetch_comments(
  videoUrl="https://www.youtube.com/watch?v=XXXXXXXXXXX",
  order="relevance",
  max=300
)

接著請模型做摘要／分類／翻譯並輸出報告。

在 MCP Inspector 測試

  • Transport：STDIO

  • Command：<abs path>/yt_mcp/.venv/bin/python

  • Arguments：<abs path>/yt_mcp/server.py

  • Environment（可選）：YOUTUBE_API_KEY=YOUR_API_KEY

輸出格式（節選）

{
  "video_id": "abcdEFGhijk",
  "order": "relevance",
  "requested": 300,
  "total_returned": 278,
  "items": [
    {
      "id": "...",
      "parentId": null,
      "author": "Somebody",
      "publishedAt": "2025-01-01T12:34:56Z",
      "likeCount": 42,
      "text": "Great video!"
    }
  ]
}

Troubleshooting

  • Missing YOUTUBE_API_KEY 在 .env 或設定的 env 補上金鑰，並確認金鑰已啟用 YouTube Data API v3。

  • 找不到 server.py 在設定裡把 args 改用絕對路徑（例如 "/Users/you/yt_mcp/server.py"）。

  • ModuleNotFoundError 確認已在虛擬環境內安裝相依套件（"mcp[cli]" httpx python-dotenv）。

  • HTTP 403/400 可能是配額不足、影片關閉留言、或金鑰權限未開。

安全

  • .env 已在 .gitignore 中，請勿提交金鑰。

  • 若曾不小心提交金鑰，請 旋轉金鑰 並清理 Git 歷史。

授權

MIT License。

Available Tools

1 tool
fetch_commentsA

Fetch public comments for a YouTube video and return a JSON string. Args: videoUrl: Full YouTube video URL. order: "relevance" (default) or "time". max: Max total comments to return (100–1000 建議).

ParametersJSON Schema
NameRequiredDescriptionDefault
videoUrlYes
orderNorelevance
maxNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so description bears full burden. It mentions 'public' but omits authentication requirements, rate limits, error handling, or side effects. Fails to disclose important behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with args list, front-loaded with purpose. No wasted words, concise yet informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema exists but description does not leverage it. Lacks mention of pagination, error responses, or field details. Adequate for simple tool but could be more complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, description adds meaning: specifies videoUrl as full URL, order options, and max range suggestion. Enhances understanding beyond schema types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'Fetch' and resource 'public comments for a YouTube video', with immediate purpose. No siblings exist, so no differentiation needed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides parameter usage (order default, max range suggestion) and notes public availability. Lacks explicit when-to-use/alternatives, but no siblings make this acceptable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools.

Naming Consistency5/5

A single tool named 'fetch_comments' follows a clear and consistent verb_noun pattern.

Tool Count3/5

One tool is borderline; it is appropriate for a highly focused purpose, but most servers benefit from at least a few related tools.

Completeness2/5

The server only provides fetching of comments, lacking common operations like replying, deleting, or retrieving replies, which are expected for a YouTube Comments server.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

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