YouTube Summarizer MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_youtube_transcriptB | Fetch the full plain-text transcript of a YouTube video. Best for agents that want all text at once. |
| search_transcriptA | Search inside a video transcript and return matching lines with timestamps. Case-insensitive. Helpful when an agent needs to find a specific topic. |
| get_timestamped_transcriptB | Return the full transcript with [MM:SS] timestamps on each line. Useful when an agent needs to cite specific moments in the video. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| summarize_video | Generate a prompt template that asks an LLM to summarize a video. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: one returns the full transcript with timestamps, one returns plain text, and one searches for specific terms. No ambiguity between them.
All tool names follow a consistent verb_noun pattern in snake_case (get_timestamped_transcript, get_youtube_transcript, search_transcript), making them predictable and easy to understand.
Three tools is well-scoped for a YouTube transcript server, covering the core needs without being too few or too many.
The set covers the main transcript retrieval and search functionality. A minor gap is the lack of a tool to get video metadata or list available transcripts, but it is still complete for typical summarization tasks.