Building an AI Assistant with YouTube Transcript MCP Server
To build an AI assistant with a YouTube Transcript MCP server, write a protocol-compliant server file, register the tools schema in your client settings, and query the assistant to analyze live video links directly inside your chat workspace.
3 Core Tools Expose by the Server
youtube_get_transcript— Fetches raw plain text from any video URL.youtube_search_keywords— Pinpoints precise timestamps where key terms are mentioned.youtube_get_srt— Exposes synced subtitle output files for editing tracks.
MCP Server JSON Integration Template
Append this block inside your client configuration (claude_desktop_config.json or config.json):
{
"mcpServers": {
"transcribeyt-mcp": {
"command": "npx",
"args": ["-y", "@transcribeyt/mcp-server"],
"env": {
"TRANSCRIBEYT_API_KEY": "your_credential_key"
}
}
}
}
Tool-Calling Capabilities
| Server Tool | Inputs Required | Output format | Main Use Case |
|---|---|---|---|
| Get Transcript | videoUrl (string) | JSON/Text | General summarization |
| Keyword Search | videoUrl, query | Timestamp array | Instant quote retrieval |
| Get Subtitles | videoUrl, format | SRT/VTT file data | Video post-production |
"Exposing media assets to agents via MCP turns standard models into expert research assistants that can analyze, query, and cite YouTube videos in real-time." — Dr. Sarah Jenkins, Chief AI Architect at Agentive