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 haljishi/vidwords-mcp --skill youtube-transcriptsgit clone --depth 1 https://github.com/haljishi/vidwords-mcpWrote 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/haljishi/vidwords-mcp/youtube-transcripts)<a href="https://agentmods.dev/skills/haljishi/vidwords-mcp/youtube-transcripts"><img src="https://agentmods.dev/badge/skills/haljishi/vidwords-mcp/youtube-transcripts/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/haljishi/vidwords-mcp/youtube-transcripts"><img src="https://agentmods.dev/badge/skills/haljishi/vidwords-mcp/youtube-transcripts.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 | $0.00111 | $0.02504 |
| Opus 5.5 | $0.00044 | $0.01002 |
| Sonnet 5.5 | $0.00022 | $0.00501 |
| Haiku 4.5 | $0.00011 | $0.00250 |
Grade A, and why
youtube-transcripts scanned grade A with 0 findings 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 15d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reading YouTube videos
A model cannot watch a video, but it can read a transcript carrying timestamps it is able to cite. So the useful unit here is not "a transcript" — it is a grounded answer with a link the user can click and check.
Prefer returning a quote plus its deep link over a wall of text.
Endpoint
Hosted MCP server, no integration code:
POST https://vidwords.com/mcp
Authorization: Basic <api-token>
Basic, not Bearer, and the token is not a base64 pair — send it verbatim.
Create one on https://vidwords.com/api-keys (the value is shown once, at creation).
Free tier included; the account's email must be verified or every call returns 403.
Clients that support MCP OAuth (Claude, ChatGPT, Cursor, VS Code, Codex) need no
token at all: give them the URL and the user signs in.
There is a plain REST equivalent at POST https://vidwords.com/api/transcripts
if MCP is not available to you — see https://vidwords.com/api-docs.
Choosing a tool
Check the Library first. search_library searches every transcript the account
has already saved, and list_library lists those videos — both free. If the user
asks about something they watched or researched before, the answer is often
already there, and fetching the video again would only repeat work.
{ "query": "pricing model" }
search_transcript is the default for a video's own words. Reach for it whenever the question is
"what does this video say about X".
{ "video": "dQw4w9WgXcQ", "query": "pricing model" }
It returns the matching moments, each with timestamp, startSeconds and a
youtube.com/watch?v=…&t=…s url. Cite those urls.
get_transcript returns the whole text and costs the same — one Cloud Request
for a video the account does not have yet, nothing for one it does. A two-hour interview
is ~20,000 words of which perhaps 300 answer the question, and the other 19,700
compete for your attention and degrade the answer. Use it only when the full text
is genuinely the deliverable: an export, a diff, a corpus.
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.
- 15d ago Changed · +13 lines 44532dc41e2d
- 16d ago Changed · +12 lines · +111 tokens per session 0c221d0e3d7e
- 17d ago Changed · +44 lines df28580c6651
- 1mo ago First seen · 128 lines · 0 tokens per session scan A e3e04a5a31e4
youtube-transcripts is a skill published in the GitHub repository haljishi/vidwords-mcp (0 stars, last pushed 3d ago), licensed MIT. It adds 111 tokens to every session and 2,504 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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