About Archivarix Tube Search
Archivarix Tube Search is an MCP service for AI clients to search archived YouTube content, including deleted videos, metadata, subtitles, and summaries. Its stdio-to-HTTP proxy exposes the remote service's tools, resources, and prompts.
Key features
- 01Discover archived videos by channel
- 02Search titles and descriptions in full text
- 03Retrieve video metadata and subtitles
- 04View or generate AI summaries
- 05Check video status-change history
Use cases
- 01Find historical videos from a channel
- 02Locate deleted videos and their subtitles
- 03Research videos and browse summaries
MCP support
The local package exposes tools, resources, and prompts to AI clients over stdio, while connecting to the remote Archivarix Tube Search MCP server using Streamable HTTP.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y tube-search-mcpTUBE_API_KEYSecretAPI key for Archivarix Tube Search. Obtain at https://tube.archivarix.net/profile (Plus tier or API tier required).Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEtube-search-mcp
MCP server for Archivarix Tube Search — search archived YouTube videos via AI assistants.
Search over 1 billion YouTube videos indexed since 2005. Find deleted videos, metadata, thumbnails, and subtitles.
Quick Start
npx tube-search-mcp --api-key tsk_YOUR_KEY
Or with environment variable:
export TUBE_API_KEY=tsk_YOUR_KEY
npx tube-search-mcp
Get your API key at tube.archivarix.net (Profile → API Keys).
Configuration
Claude Desktop
Add to ~/.claude/claude_desktop_config.json:
{
"mcpServers": {
"tube-search": {
"command": "npx",
"args": ["-y", "tube-search-mcp"],
"env": {
"TUBE_API_KEY": "tsk_YOUR_KEY"
}
}
}
}
Claude Code
Add to ~/.claude/mcp.json:
{
"mcpServers": {
"tube-search": {
"command": "npx",
"args": ["-y", "tube-search-mcp"],
"env": {
"TUBE_API_KEY": "tsk_YOUR_KEY"
}
}
}
}
VS Code
Add to .vscode/mcp.json in your project:
{
"servers": {
"tube-search": {
"command": "npx",
"args": ["-y", "tube-search-mcp"],
"env": {
"TUBE_API_KEY": "tsk_YOUR_KEY"
}
}
}
}
Cursor
Add to ~/.cursor/mcp.json:
{
"mcpServers": {
"tube-search": {
"command": "npx",
"args": ["-y", "tube-search-mcp"],
"env": {
"TUBE_API_KEY": "tsk_YOUR_KEY"
}
}
}
}
Available Tools
| Tool | Description |
|---|---|
search_channel | Find all archived videos from a YouTube channel |
search_videos | Full-text search across video titles and descriptions |
get_video | Get metadata for a specific video by ID |
get_subtitles | Get transcript as readable plain text |
get_summary | Get AI-generated video summary |
generate_summary | Generate a new AI summary for a video |
browse_summaries | Browse summaries by tag, channel, or language |
get_video_status_history | View status change history of a video |
get_usage | Check your current API usage and limits |
Resources
| URI | Description |
|---|---|
tube://video/{videoId} | Video metadata |
tube://channel/{channelId} | Channel info |
tube://subtitles/{videoId} | Transcript as plain text |
tube://summary/{videoId} | AI-generated summary |
tube://tags | Popular summary tags |
Prompts
| Prompt | Description |
|---|---|
research_video | Comprehensive video analysis workflow |
channel_overview | Channel research and statistics |
find_deleted | Discover and analyze deleted videos |
Environment Variables
| Variable | Description | Default |
|---|---|---|
TUBE_API_KEY | API key (required) | — |
TUBE_MCP_URL | Custom MCP endpoint | https://tube.archivarix.net/mcp |
How It Works
This package acts as a stdio-to-HTTP proxy. It connects to the remote Archivarix Tube Search MCP server via Streamable HTTP and exposes the same tools, resources, and prompts over stdio transport for local AI clients.
AI Client ←(stdio)→ tube-search-mcp ←(HTTP)→ tube.archivarix.net/mcp
Documentation
Full documentation: tube.archivarix.net/guide/mcp
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.