Model Context Protocol

Your agent can write the code.
It has never seen a good launch video.

STEALSHOT indexes 160 launch videos, product films, demos and podcast intros frame by frame. Every frame has been described for its craft, how it is framed, lit, typeset and cut, so an agent can search by what a shot looks like rather than by title. 15,461 frames, 108 brands.

Install

Claude Code

claude mcp add stealshot --scope user --transport http https://stealshot.com/api/mcp

Cursor

{
  "mcpServers": {
    "stealshot": {
      "url": "https://stealshot.com/api/mcp"
    }
  }
}

Codex

codex mcp add stealshot --transport http https://stealshot.com/api/mcp

No API key and no account. The library is public and every tool is read only.

6 tools

search_frames

Search the frame library by what is actually IN and TRUE OF a shot. This is the main way in. Every frame has been described by a vision model, so plain language works: 'presenter against a dark backdrop with the UI floating beside them', 'code on a light background with huge negative space', 'title card that opens on the wordmark'. Combine free text with the filters to narrow by craft.

query · technique · subject · surface · shot_type · tone · brand · launch_only · opening_only · limit

find_pattern

Given a technique or a plain-language move, gather the EVIDENCE for it across different videos: one best example per brand, plus how widespread it is. This is the tool for 'is this a real convention or did one video do it once', and for building an argument rather than a single reference. Always prefer this over search_frames when the question is about a pattern rather than a picture.

technique · query · limit

list_techniques

List the technique vocabulary the library actually uses, with how many frames and how many distinct videos use each. Call this before search_frames when you want to filter precisely, or to answer 'what moves are common in launch videos'. A technique used by many DIFFERENT videos is a convention; one used many times inside a single video is that video's habit, so both counts are returned.

contains · min_videos · limit

get_video

The full anatomy of one video: its measurements plus a shot-by-shot walk through its described frames in time order. Use this after search_frames when a single reference is worth studying properly, or to answer 'how is this video actually built'. Prefer it over many search calls on the same title.

video_id · title · max_frames

compare_brands

Compare how two or more brands cut their videos: pace, how much of the frame is a face, how dark they shoot, and their most-used techniques. Use for 'how does Linear's launch style differ from OpenAI's'.

brands

library_stats

What is actually in the library right now: counts, the brands with the most indexed videos, and how much of it has been described. Call this first if you need to know whether a question is answerable, and to avoid claiming coverage the corpus does not have.

no arguments

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