YouTube Comment Downloader MCP Server

by suckerfish

316 downloads

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GitHub

Media

About

YouTube Comment Downloader MCP server that allows AI systems to download and analyze YouTube video comments without requiring API keys

Details

Author: suckerfish
Downloads: 316
Categories: Media

- Four specialized tools for different comment analysis needs
- No authentication required – uses web scraping
- Context-efficient statistics tool (~200 tokens vs ~25,000 for full data)
- Built-in capacity planning with memory and timeout limits
- Engagement analysis with actual like-count sorting

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name YouTube Comment Downloader MCP Server

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

From the repository

Install dependencies with uv venv && source .venv/bin/activate && uv pip install -e ., test with python test_server.py, and run the server with python src/server.py. For MCP clients (e.g., Claude Desktop), add a configuration block using uv as the command pointing to src/server.py. The server exposes four tools: download_youtube_comments, get_comment_stats, search_comments, and get_top_comments_by_likes.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "youtube comment downloader mcp server": {
            "ytcomment_mcp": {
                "command": "uv",
                "args": [
                    "venv",
                    "&&",
                    "source",
                    ".venv/bin/activate"
                ]
            }
        }
    }
}

McpServers

{
    "ytcomment_mcp": {
        "command": "uv",
        "args": [
            "venv",
            "&&",
            "source",
            ".venv/bin/activate"
        ]
    }
}

YouTube Comment Downloader MCP Server

A Model Context Protocol (MCP) server that provides AI systems with the ability to download and analyze YouTube video comments without requiring API keys.

Features

- 4 specialized tools for different comment analysis needs
- No authentication required - uses web scraping
- Context-efficient statistics tool to avoid token bloat
- Built-in capacity planning with memory and timeout limits
- Engagement analysis with actual like-count sorting

MCP Client Configuration

Add this configuration block to your MCP client (e.g., Claude Desktop):

"ytcomment-mcp": {
  "command": "uv",
  "args": [
    "run",
    "--directory",
    "/Users/chad.kunsman/Documents/PythonProject/ytcomment_mcp",
    "src/server.py"
  ]
}

Available Tools

1. `download_youtube_comments`

Download raw comment data with full details. - Parameters: video_id, limit (1-10000), sort (0=popular, 1=recent) - Returns: Full comment dataset with all metadata - Use case: When you need complete comment data for analysis

2. `get_comment_stats`

Get statistical analysis without full comment data (context-efficient). - Parameters: video_id, limit, sort - Returns: Statistics + 5 sample comments (~200 tokens vs ~25,000) - Use case: Quick engagement insights without context bloat - Triggers: "how engaged", "what's the engagement", "comment patterns"

3. `search_comments`

Search for specific terms within comments. - Parameters: video_id, search_term, limit, sort - Returns: Matching comments + search metadata - Use case: Finding mentions, sentiment analysis, topic research - Triggers: "find comments about", "search for", "mentions of"

4. `get_top_comments_by_likes`

Get most-liked comments sorted by actual like count (not YouTube's "popular"). - Parameters: video_id, top_count (1-100), sample_size (100-2000, default: 500) - Returns: Top comments ranked by likes + engagement stats - Use case: Finding viral comments that YouTube's algorithm might not surface first - Triggers: "most popular", "most liked", "viral comments", "best comments"

Quick Start

```bash

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About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

YouTube Comment Downloader MCP Server

Features

MCP Client Configuration

Available Tools

1. download_youtube_comments

2. get_comment_stats

3. search_comments

4. get_top_comments_by_likes

Quick Start

Install

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1. `download_youtube_comments`

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4. `get_top_comments_by_likes`