Server data from the Official MCP Registry
Extract YouTube transcripts, search what was said, and read on-screen frames with cited timestamps.
About
Extract YouTube transcripts, search what was said, and read on-screen frames with cited timestamps.
Remote endpoints: streamable-http: https://vidwords.com/mcp
Security Report
Valid MCP server (2 strong, 4 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
Endpoint verified · Requires authentication · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"com-vidwords-youtube": {
"url": "https://vidwords.com/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
VidWords YouTube MCP Server
A hosted Model Context Protocol server that lets an AI agent read YouTube videos — and cite the exact second it got the answer from.
A language model cannot watch a video. Point it at this endpoint and it gains nine tools for searching transcripts, reading a video's frames — slides, charts, demos, on-screen text — and answering questions with citations that are verified before you see them.
No integration code. No scraping. No proxy pool.
POST https://vidwords.com/mcp
Authorization: Basic <your-api-token>
Remote-only and hosted — there is nothing to install or self-host. This repository is the public manifest, configuration reference and issue tracker for that endpoint.
Quick start
Most clients need no token at all. The server speaks OAuth, so the client registers itself, sends you to VidWords to sign in, and stores a credential it refreshes on its own. You can create the account during that sign-in step. The free plan includes monthly credits and 10 Watch minutes, so you can wire this up and use it before paying anything.
claude.ai, ChatGPT and Claude Desktop — add a connector, nothing to paste
Add this as a custom connector:
https://vidwords.com/mcp
The host registers itself, sends you to VidWords to sign in, and shows a consent screen naming exactly what it is asking for. Registration alone grants nothing — access begins only when a signed-in person clicks Approve, and live connections can be revoked from your API page with immediate effect.
Claude Code
claude mcp add --transport http vidwords https://vidwords.com/mcp
Then type /mcp in a session and choose Authenticate.
Cursor — .cursor/mcp.json
{
"mcpServers": {
"vidwords": {
"url": "https://vidwords.com/mcp"
}
}
}
Cursor shows the server as Needs login — click that once and it runs the OAuth flow in your browser. Because this file carries no secret, it is safe to commit, which the header form below is not.
A static token instead
For CI, a container, or a client with no OAuth support, authenticate with a header. Create an account at vidwords.com/register, verify your email, then copy the token from your profile.
Claude Code
claude mcp add --transport http vidwords https://vidwords.com/mcp \
--header "Authorization: Basic YOUR_API_TOKEN"
Claude Desktop — claude_desktop_config.json
{
"mcpServers": {
"vidwords": {
"type": "http",
"url": "https://vidwords.com/mcp",
"headers": { "Authorization": "Basic YOUR_API_TOKEN" }
}
}
}
Cursor — .cursor/mcp.json
{
"mcpServers": {
"vidwords": {
"url": "https://vidwords.com/mcp",
"headers": { "Authorization": "Basic YOUR_API_TOKEN" }
}
}
}
Keep this out of version control, or use ~/.cursor/mcp.json instead — the header holds a live
credential.
Codex CLI — ~/.codex/config.toml
[mcp_servers.vidwords]
url = "https://vidwords.com/mcp"
env_http_headers = { "Authorization" = "VIDWORDS_MCP_AUTH" }
export VIDWORDS_MCP_AUTH="Basic YOUR_API_TOKEN"
Do not use
bearer_token_env_var. It is the obvious-looking field, but it sendsAuthorization: Bearer <value>and this server authenticates with Basic.
Clients without custom-header support, and Docker
This repository also ships a small stdio proxy (src/index.js) that speaks MCP on
stdin/stdout and forwards tool calls to the hosted endpoint. Use it when your client cannot
send a custom HTTP header, or when you want the server in a container:
{
"mcpServers": {
"vidwords": {
"command": "npx",
"args": ["-y", "github:haljishi/vidwords-mcp"],
"env": { "VIDWORDS_API_TOKEN": "YOUR_API_TOKEN" }
}
}
}
Run straight from this repository — the proxy is not published to npm, so a bare
npx @vidwords/mcpwill not resolve.
docker build -t vidwords-mcp .
docker run --rm -i -e VIDWORDS_API_TOKEN=YOUR_API_TOKEN vidwords-mcp
The tool schemas are declared inline in the proxy, so initialize and tools/list answer
without any credentials and the upstream is not contacted until a tool is actually called.
A call without VIDWORDS_API_TOKEN returns a readable error rather than failing the
handshake. VIDWORDS_MCP_URL overrides the endpoint if you are pointing at a non-production
instance.
The generic mcp-remote bridge works too:
{
"mcpServers": {
"vidwords": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://vidwords.com/mcp",
"--header", "Authorization:Basic YOUR_API_TOKEN"]
}
}
}
Ready-made config files live in examples/.
The nine tools
| Tool | What it does | Cost |
|---|---|---|
search_transcript | Find where a video discusses something. Takes one video or a list of up to 25, so one call can answer a question across a whole channel. Returns the matching moments with timestamps, quoted context, and youtube.com/watch?v=…&t=…s deep links. | 1 credit per video |
get_transcript | Full transcript text for up to 25 videos in one call. | 1 credit per video |
list_channel_videos | Resolve a channel handle, URL or UC… id to its recent uploads. | Free · Starter and up |
list_watchlists | The account's Radar watchlists and how much each has recorded. | Free |
watchlist_activity | Newest uploads Radar has recorded for one watchlist. | Free |
account | Plan and remaining credits, so the agent can price a job before running it. | Free |
analyze_video | Start a frame-level analysis — slides, charts, demos and on-screen text, not just captions. Returns an analysisId immediately. | Watch minutes |
get_analysis | Read a finished analysis: chapters, key points, timestamped evidence. | Free |
ask_video | Ask a question against a finished analysis. Citations are verified against stored evidence or dropped. | 1 Watch question |
Prefer search_transcript over get_transcript
Both cost one credit per video, so there is no billing reason to choose. The reason is context.
Ask "what did this two-hour interview say about pricing?" and get_transcript returns roughly
20,000 words, of which perhaps 300 are about pricing — those 300 now compete for attention with
19,700 that are not, and the answer gets worse, slower and more expensive to generate.
search_transcript returns only the matching stretches, each with a deep link. Reach for
get_transcript when you genuinely want the whole text: an export, a diff, a corpus.
Ask for a span, not a whole video
Both transcript tools take optional from and to timecodes — seconds (615), m:ss
(10:20) or h:mm:ss (1:02:13):
{ "videos": ["dQw4w9WgXcQ"], "from": "10:20", "to": "11:00" }
These are the same formats the tools print back, so a timestamp out of one answer can be pasted straight into the next question. A timecode that cannot be parsed is refused before anything is fetched, so a typo costs no credit — it never silently widens to the whole video.
One call across a channel
search_transcript accepts a list, which is how you answer "what has this channel said about
X" without a round trip per video. Get the ids from list_channel_videos first:
{ "video": ["VIDEO_ID_1", "VIDEO_ID_2", "VIDEO_ID_3"], "query": "pricing" }
Each video is billed at the usual 1 credit, and one unavailable video is reported in its own row rather than failing the call — the others were fetched and charged for, so you still get them.
It reads the picture, not only the captions
analyze_video looks at slides, charts, code samples and on-screen text that is never spoken
aloud. ask_video then answers against that stored analysis, and every citation is checked
before you see it: a visual claim has to match a frame that was actually recorded, a spoken
claim has to land on a real transcript segment. Anything that fails is dropped, and when nothing
survives the answer says the evidence is insufficient rather than producing a confident guess.
That is occasionally annoying — a refusal is a worse demo than a fluent answer — and it is the only version of this feature that is safe to put in front of an agent, because an agent repeats what it is told without the scepticism a human reader applies.
Auth, cost and limits
- If you pasted a token:
Basic, notBearer. The token is sent as-is; you do not base64-encode auser:passpair. Clients that signed in carry their own credential and this does not apply. - Verify your email first. Until you click the verification link every call returns
403with{"error":"email_unverified"}— the most common first-call failure on a new account. - Credits are one pool shared with the REST API and the website. One credit is one transcript. Frame analysis draws Watch minutes instead, and a run refused before it starts costs nothing.
- Rate limit: 30 requests / 10s — deliberately looser than the REST API's 5, because the server
is stateless and a client re-runs
initializebefore every call.analyze_videohas its own ceiling of 10 starts per minute, shared with the REST route. - RapidAPI tokens are refused here. That identity is metered per call and has no account behind it, neither of which survives a tool-calling session. Use a VidWords API token.
- Stateless by design. No resumable SSE streams, no session to delete; every tool answers in
one shot.
GETandDELETEreturn a JSON-RPC error rather than an HTML 404. - Captions have to exist. For a video with no caption track, a signed-in account can transcribe from audio instead — priced by length, quoted before you spend.
Full numbers: pricing.
Agent skill
skills/youtube-transcripts/SKILL.md is a drop-in agent
skill for this server — tool selection, timecode spans, channel-wide search, the cost table and
the error codes worth acting on, in the format Claude and compatible agents load directly.
Copy the folder into your agent's skills directory:
git clone --depth 1 https://github.com/haljishi/vidwords-mcp
cp -r vidwords-mcp/skills/youtube-transcripts ~/.claude/skills/
It assumes the MCP server is configured (see Quick start). The point of it is that an assistant
which has read the skill knows to reach for search_transcript with a timecode span instead of
pulling a whole two-hour transcript into its context.
Documentation
- Agent skill (SKILL.md)
- YouTube MCP server — overview
- Setup in Claude Code
- Setup in Claude Desktop
- Setup in Cursor
- REST API documentation
Support
Open an issue here for anything about the MCP surface — a tool that misbehaves, a client whose config we have not documented, a schema that could be clearer. Account and billing questions go to support.
License
The contents of this repository (documentation and configuration examples) are MIT licensed. The hosted service itself is proprietary and governed by the VidWords terms.
Independent product; not affiliated with YouTube or Google.
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