How to Get YouTube Transcripts with an AI Agent Using Skill or MCP

What do you need from the video's transcript?

A video link can become a useful research input when your agent can retrieve the available transcript and show which passages support its answer. You might need a five-point summary, a list of product claims, or a passage to check before quoting a speaker.

Start with the Glasser Skill in your existing agent. The workflow below retrieves one video's transcript, checks the returned text, and then asks the agent to summarize it. MCP is the connection option for supported assistants that use that path.

The video, language, and question define the request

Provide a YouTube video URL, your preferred transcript language, and the question you want answered. “Summarize the speaker's explanation of usage-based pricing” gives the agent something more specific to verify than “summarize this video.”

Glasser's YouTube transcript operation, provided by ScrapeCreators, requires url and accepts an optional language. It publishes no fixed output schema. Ask the agent to inspect the current contract and then check what text and timing information actually arrive.

Transcript retrieval and summary writing are separate steps

The transcript supplies text for the agent to analyze. A summary is the agent's interpretation of that text, so preserve the retrieved material before asking for conclusions or quotations.

Generating a new transcription from audio is a different task. A missing transcript should lead to a clear explanation of what is unavailable; the prompt below requires the agent to ask before purchasing another operation. Translation also needs to be distinguished from retrieving an existing language track.

Should you connect through Skill or a YouTube transcript MCP server?

The Glasser Skill is the starting point for local agents

Paste this into Claude Code, Codex, Cursor, or another compatible local agent:

set up https://glasser.ai/SKILL.md

Follow the official guide for your client. Local setup saves the Skill, prepares the CLI, and uses browser sign-in. It needs terminal and internet access and Node.js 22 or newer; the guide helps the agent check those requirements.

Confirm the connection before retrieving video data:

Use Glasser to confirm my available balance.
Make no paid transcript requests.

You can then stay in the same agent and describe the video task. A separate transcript library or custom server is unnecessary for the path described here.

Glasser MCP exposes the same data workflow to supported assistants

Follow your assistant's Glasser MCP setup guide. The server address is:

https://api.glasser.ai/mcp

Supported OAuth clients take you through sign-in and Workspace selection. Verify access with a balance-only request. The Skill setup entry also guides supported cloud assistants through their connection steps.

Glasser's MCP tools discover provider operations, inspect their contracts, and run the selected operation. You can use that connection for the one-video transcript task without adding a dedicated YouTube transcript MCP server. Features such as playlist traversal, video search, or subtitle management need their own capability checks.

What should you ask before retrieving the transcript?

Confirm the language, operation, and current charge

Have the agent show whether the selected operation supports your video URL and requested language input, together with its price and no-result terms. Search and Inspect are free. The inspected transcript operation charges per request and can charge for no result, so a successful connection check does not imply that retrieval is free.

The supported Glasser inputs are url and optional language. Parameters mentioned in a provider's separate documentation are usable through Glasser only if the Glasser contract exposes them. Your agent should not add undocumented options to obtain audio transcription or change cache behavior.

A prompt for one transcript and a grounded summary

Replace the bracketed inputs:

Use the installed Glasser Skill to retrieve the transcript for
this YouTube video: [video URL].
My preferred transcript language is [language].
My question is: [what you want to understand from the video].

Inspect the transcript operation. Show the supported inputs,
current price, and no-result terms. Wait for my approval
before a paid Run.

After approval, retrieve this video's transcript only.
Preserve the returned text before writing a five-point answer.
For each point, identify the passage that supports it.
Include the video link. Use timestamps only if the returned
timing data can be interpreted; do not invent timing or quotes.

If the transcript or requested language is unavailable,
report that and stop. Ask before another language request,
another source, or paid audio transcription.

Include the Run URL, status, provider outcome, and final charge.

This prompt is an editorial workflow recommendation. For an MCP connection, change its opening to “Use the connected Glasser MCP tools”; keep the task and evidence requirements intact.

How do you check the transcript and its summary?

A usable transcript needs text, provenance, and clear gaps

Before relying on a summary, ask the agent to explain what it received:

Apply this review checklist to the actual response. If the agent cannot establish completeness from the available data, it should say that completeness remains unverified. A long block of text alone cannot prove that nothing was omitted.

Timestamps and quotations need a closer check

Use timestamps only after the agent has established the meaning and units of the returned time fields. If the response supplies text without usable timing, retain the video URL and supporting passages and leave timestamp links out.

For quotations, compare the proposed wording with the retrieved text. If the exact spoken wording matters, check the original video as well: the transcript is evidence to inspect, and this guide does not establish its accuracy against the audio.

The Python transcript guide serves readers implementing retrieval in code. This workflow keeps the connection, retrieval, and review inside the agent conversation.

What happens when captions are missing or the request fails?

Missing captions and failed retrievals need different explanations

Ask the agent to report the Run status, what the provider returned, and the actual charge. A COMPLETED Run can contain a provider error, as described in Glasser's result guidance. Check the response before treating an empty answer as evidence that no transcript exists.

If the requested language is unavailable, the next decision is yours: stop, consider an available language, or investigate a separate transcription task. Each additional retrieval should have a reason and a price. The prompt above makes that decision explicit.

Further questions can start from the text already retrieved

Once you have the transcript, ask focused follow-ups such as “Which claims concern pricing?” or “Which questions does the speaker leave unanswered?” Ask the agent to use the text already in the conversation and identify the passages behind its answer.

For a second video, ask for a new retrieval plan before comparing the two. For a lost connection, have the agent recover the original Run with its original idempotency key and unchanged execution parameters before creating another purchase.

You can set up the Glasser Skill and start with one video, one question, and a report you can check against the text.

Documentation and the transcript contract were checked October 15, 2026. No paid transcript retrieval was performed for this guide, and transcript accuracy or timestamp behavior has not been tested against a video.

Questions about YouTube transcripts with Skill or MCP

Do I need a separate YouTube transcript MCP server?

Glasser MCP can connect your assistant to the available transcript operation through its general tools. A dedicated server may offer additional functions, so check those separately if your task extends beyond the one-video workflow here.

Can an agent retrieve transcripts from every public video?

Availability depends on the video, language, and selected data source. Ask the agent to report any missing or unusable text and avoid treating a failed request as proof that no captions exist.

Will the agent automatically transcribe missing audio?

The prompt in this guide tells it to stop when the requested transcript is unavailable. A separate audio-transcription task requires a verified operation, an explanation of the scope and charges, and your authorization to proceed.