MCP recipes

Prompts that work well, and the tool calls they lead to. You do not have to name the tools. Describe the job and the agent picks them. If it reaches for a full transcript too early, tell it to start with the overview.

Summarize a talk and find where a topic comes up

Summarize https://www.youtube.com/watch?v=VIDEO_ID in five bullets. Then find where they discusspricing, quote what they say, and give me the link to that moment.

The agent:

1. Calls get_video_context with the default brief detail for the summary, chapters and key moments.
2. Calls search_video with "pricing" for the matching moments.
3. Calls get_transcript with from and to set a minute either side of the best hit.
4. Answers with a quote and a youtu.be/VIDEO_ID?t=... link.

Nothing here reads the whole transcript, so it stays cheap even for a long video.

Compare two videos

Compare these two talks on how they handle onboarding. Where do they agree, where do they differ?Link the moments you rely on.https://www.youtube.com/watch?v=FIRST_IDhttps://www.youtube.com/watch?v=SECOND_ID

The agent calls get_video_context for each video, then ask_video on both with the same question, for example "What does the speaker recommend for a user's first session?". Each answer comes with cited moments it can link. Starting from the brief overview keeps both videos in the agent's context at once.

Pull the steps out of a tutorial

A tutorial often shows the steps and says little about them. Ask about what is shown, so Scribiz looks at the picture. This needs an API key on the remote server, or a credential on the local one. Without a key the remote server never looks at the picture, so you get the steps that are spoken, and a question about what was shown is answered from the words only.

Watch https://www.youtube.com/watch?v=VIDEO_ID and write the steps as a numbered list with theexact menu names and commands that appear on screen. Add the time of each step.

The agent calls ask_video with a question about what is on screen, and get_video_context with include set to chapters and on_screen. Scribiz watches a video when it has little speech, when it is a short clip, and when a question about the picture needs it. With a key, or on the local server, the agent can also pass watch: true to get_video_context or ask_video, which reads the picture of a talk that has normal speech (see Watch, with a key). Without a key the remote server does not look at the picture, so ask about what is shown and the agent gets what is said about it. On-screen text is a model's reading of the picture, so tell the agent to check anything critical against the transcript.

Find a decision in a recording on your disk

This one needs the local server, which needs the command-line tool and a credential: a free Scribiz account or your own Gemini key (npm install -g scribiz, then scribiz login or scribiz setup). Start the server with the folder allowed:

claude mcp add scribiz -- scribiz mcp --allow-files --root ~/Recordings

In ~/Recordings/standup-oct-3.mp4, what did we decide about the launch date, and who agreed to it?

The agent passes the path to ask_video. The audio is cut on your machine and goes to Google with your key. The video itself does not. A file outside the folders you allowed is refused with an error that names them.

Turn a video into notes

Make study notes from https://www.youtube.com/watch?v=VIDEO_ID. Use the chapter titles as headings,keep the key points under each, and put the timestamp link next to every point.

get_video_context with detail: "standard" already holds the chapters, key moments and entities with their times, so this is usually one call. A video with no chapters falls back to the key moments.

Habits that help

• Say what you need. "The pricing discussion" beats "everything".
• Name the time range if you know it. get_transcript takes from and to.
• Ask for links. They make the answer checkable.
• Tell the agent to treat the transcript as data and not as instructions. See Security.