Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add krusemediallc/cursor-ad-agent --skill pixar-style-ad-arcads-mcpgit clone --depth 1 https://github.com/krusemediallc/cursor-ad-agentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/krusemediallc/cursor-ad-agent/pixar-style-ad-arcads-mcp)<a href="https://agentmods.dev/skills/krusemediallc/cursor-ad-agent/pixar-style-ad-arcads-mcp"><img src="https://agentmods.dev/badge/skills/krusemediallc/cursor-ad-agent/pixar-style-ad-arcads-mcp/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/krusemediallc/cursor-ad-agent/pixar-style-ad-arcads-mcp"><img src="https://agentmods.dev/badge/skills/krusemediallc/cursor-ad-agent/pixar-style-ad-arcads-mcp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00098 | $0.04410 |
| Opus 5 | $0.00049 | $0.02205 |
| Sonnet 5 | $0.00020 | $0.00882 |
| Haiku 4.5 | $0.00010 | $0.00441 |
Grade A, and why
pixar-style-ad-arcads-mcp scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
2. `PUT` the bytes: `curl -s -o /dev/null -w "%{http_code}\n" -X PUT -H "Content-Type: image/png" --upload-file "<file>" "<presignedUrl>"` → expect `200`. How it starts
The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pixar-Style Ad — Arcads MCP
Build a Disney-Pixar-style 3D animated product ad fully on the Arcads MCP server.
Same proven creative pipeline as the REST pixar-style-ad guide — gpt-image-2
storyboard → Seedance 2.0 image-to-video → VO → stitch → captions — but every API
step is an Arcads MCP tool call. The MCP handles auth and job orchestration, so
there's no hand-rolled HTTP Basic header or POST /v2/... plumbing.
⚠️ Remote-client caveat (read first). The MCP server cannot read local disk unless the client provides explicit filesystem bridging. In Cursor, every reference file (a user product photo, a generated still you chain into the next call, a clip you feed into stitch) must be uploaded via
arcads_get_upload_url+ an HTTPPUTfirst, then referenced by the returned S3filePath. TempfilePaths are single-use. And keep a.envwithARCADS_BASIC_AUTHfor the polling fallback. See Uploading & fetching.
REST pixar-style-ad step |
MCP replacement |
|---|---|
POST /v2/images/generate (gpt-image-2) + presigned upload of each reference |
arcads_generate_image_gpt (model gpt-image-2); references via arcads_get_upload_url + PUT → S3 filePath (see Uploading) |
POST /v2/videos/generate (seedance-2.0) with startFrame URL |
arcads_generate_video_seedance_20 with referenceImages:[still] (i2v) |
| ElevenLabs TTS VO | arcads_text_to_speech (one voiceId across all beats) — or keep ElevenLabs if the user insists |
GET /v1/assets/{id} polling (+ "Seedance polls /assets not /videos" gotcha) |
arcads_watch_asset (status + download URL) — gotcha gone |
ffmpeg -f concat stitch |
arcads_stitch_videos (2–6 clips/call) — or ffmpeg |
.ass / HyperFrames caption burn |
arcads_add_subtitles (style catalogue) — or HyperFrames for exact brand styling |
Manual Authorization: $ARCADS_BASIC_AUTH header on every call |
MCP injects auth — you only need .env for the polling fallback |
What does not change vs REST: reference files are still uploaded per call and
temp filePaths are still single-use (see Uploading below). What the MCP does remove:
hand-rolled auth headers, the "Seedance polls /v1/assets not /v1/videos" gotcha
(arcads_watch_asset abstracts it), and N-parallel-POSTs for variations (nbGenerations).
The only non-MCP step: muxing the VO mp3 onto each silent clip + tight-trimming
to kill dead space. No single Arcads MCP tool muxes a standalone audio track onto a
video, so that one step uses local ffmpeg.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 203 lines · 98 tokens per session scan A ec2dad5d4965
pixar-style-ad-arcads-mcp is a skill published in the GitHub repository krusemediallc/cursor-ad-agent (10 stars, last pushed 1mo ago), licensed MIT. It adds 98 tokens to every session and 4,410 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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