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 thirteen tools for
searching transcripts, searching the videos you have already saved, 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.
That URL is the whole configuration. Clients sign in over OAuth — no key to find or paste — and
headless ones can send Authorization: Basic <your-api-token> instead.
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 25 Cloud Requests and 200 AI Units a
month, so you can wire this up and use it before paying anything.
Claude (claude.ai and Claude Desktop)
- Customize → Connectors, then + Add → Add custom connector.
- URL:
https://vidwords.com/mcp
- Under the OAuth client options choose Register automatically. VidWords registers each
connector itself (dynamic client registration), so Claude's default "published identity"
option will not connect.
- Connect, sign in to VidWords, and approve.
On a Team or Enterprise plan an owner adds it first, under Organization settings → Connectors →
Add → Custom → Web; members then connect from Customize → Connectors.
ChatGPT
- On chatgpt.com, open Plugins, select +, then Add custom MCP server.
- Name:
VidWords · Server URL: https://vidwords.com/mcp · Authentication: OAuth.
- Accept the risk warning and select Create as a plugin, then sign in to VidWords and approve.
- Install the new plugin, then type
@ in a chat and pick VidWords.
Do this on the web; on a workspace account an admin may need to allow custom MCP servers.
Either way, 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 the
API & MCP page
with immediate effect.
Claude Desktop from a config file
claude_desktop_config.json only runs local (stdio) servers — a remote url entry there is
not supported (and has been reported to wipe the file's mcpServers section). To declare the
server in the file anyway, bridge it with mcp-remote,
which runs the same sign-in flow in your browser — still nothing to paste:
{
"mcpServers": {
"vidwords": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://vidwords.com/mcp"]
}
}
}
Quit and reopen Claude Desktop after editing the file.
Claude Code
claude mcp add --transport http vidwords https://vidwords.com/mcp
Then type /mcp in a session and choose Authenticate.
Cursor — one click, or .cursor/mcp.json
Use the Add to Cursor button above, or:
{
"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.
VS Code
Use the Add to VS Code button above, or put this in .vscode/mcp.json:
{
"servers": {
"vidwords": { "type": "http", "url": "https://vidwords.com/mcp" }
}
}
VS Code asks you to sign in the first time the server starts.
Codex CLI
codex mcp add vidwords --url https://vidwords.com/mcp
codex mcp login vidwords
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 create a key on the
API & MCP page.
A key's value is shown once, when it is created.
Claude Code
claude mcp add --transport http vidwords https://vidwords.com/mcp \
--header "Authorization: Basic YOUR_API_TOKEN"
Claude Desktop — claude_desktop_config.json
The same mcp-remote bridge as above, with the key instead of the sign-in. Keep the key in
env: Claude Desktop on Windows (and Cursor, and the Codex CLI) do not escape spaces inside
args, so Basic YOUR_API_TOKEN written there splits in two — the mcp-remote README's own
workaround:
{
"mcpServers": {
"vidwords": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://vidwords.com/mcp",
"--header", "Authorization:${VIDWORDS_MCP_AUTH}"],
"env": { "VIDWORDS_MCP_AUTH": "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 sends
Authorization: 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/mcp will 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. Resource discovery is also local; the upstream is contacted when a tool, prompt, or UI resource is requested.
The proxy also exposes the analysis and account MCP Apps resources. Compatible hosts can render
interactive cards; the analysis card includes Show full analysis. UI resource reads and tool
calls use the same authenticated upstream, and structured results pass through unchanged.
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:${VIDWORDS_MCP_AUTH}"],
"env": { "VIDWORDS_MCP_AUTH": "Basic YOUR_API_TOKEN" }
}
}
}
Ready-made config files live in examples/.
Two balances pay for them: a Cloud Request fetches one video's transcript, and AI Units
pay for reading frames and for transcribing audio — a fresh frame analysis spends one of each kind:
1 Cloud Request for its transcript, plus AI Units per minute of video. A video the account has already fetched is in
its Library, and reading it again is free — another time range, another page, a search after a
fetch. Every metered result reports what it charged.
| 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. Optional from/to. | 1 Cloud Request per new video |
get_transcript | Transcript text for up to 25 videos, or the span between two timecodes. lang picks a caption track, maxChars pages a long transcript, source: "audio" transcribes the speech itself. | 1 Cloud Request per new video |
search_library | Full-text search across every transcript the account has already saved, with timestamps and deep links. | Free |
list_library | The account's saved videos, newest first, plus the latest finished analysis ID. | Free |
list_analyses | Saved AI Watch analyses with IDs, status and result links; supports pagination and video filtering. | Free |
list_languages | The caption tracks a video has, and which are auto-generated (the speech) versus uploaded (possibly translations). | Free |
list_channel_videos | Resolve a channel handle, URL or UC… id to its recent uploads. | 1 Cloud Request · 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 both balances, 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. mode is quick, smart, deep or auto; Deep runs on any plan with enough AI Units. estimateOnly: true returns the price instead, without starting anything. | 1 Cloud Request, then AI Units per minute: Quick 2.8, Standard 4, Deep 30 · estimate free |
get_analysis | Read a finished analysis: overview, chapters, key points, timestamped evidence and steps. Omit analysisId to open the latest finished result. waitSeconds (up to 25) holds the call until it is ready instead of polling. | Free |
ask_video | Ask a question against a finished analysis. Citations are verified against stored evidence or dropped. | 6 AI Units per question |
Check the Library first
search_library and list_library read what the account already has, for nothing. An agent
that searches the Library before fetching a video again answers "what did that interview I
watched last week say about pricing" without spending anything, and without the round trip.
Prefer search_transcript over get_transcript
Both cost one Cloud Request per new 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 nothing — it never silently widens to the whole video.
Page a long transcript instead of guessing ranges
get_transcript takes maxChars. A result cut short says truncated: true and carries
nextFrom, the second to continue from; pass it back as from. The cut always lands between
captions, and every page after the first is a re-read of a video already in the Library — free.
{ "videos": ["dQw4w9WgXcQ"], "maxChars": 20000 }
Which language you got, and why
A caption track's language is not necessarily the language spoken. An auto-generated track
transcribes the speech; an uploaded one may be a translation — some videos carry a dozen
community translations and no track in the language actually spoken. So every transcript says
why it is the track it is:
selectionReason: requested, spoken_language (it matches the speech), caption_fallback
(no track is known to match the speech — English, if present, was picked for readability),
translated or audio_transcription.
spokenLanguage: the language being spoken when it is known, otherwise null — not a guess.
lang asks for a track. If the video has none in that language, get_transcript answers
language_unavailable with the availableLanguages it does have, and charges nothing.
source: "audio" transcribes what is said instead of reading captions — the way to get the
original words when every caption is a translation. It is priced like any audio transcription
(3 AI Units per minute of video, on top of the Cloud Request) and passing it is the consent.
list_languages answers the same question for free, from what is already stored.
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 new video is billed at the usual 1 Cloud Request, 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, not Bearer. The token is sent as-is; you do not base64-encode
a user:pass pair. 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
403
with {"error":"email_unverified"} — the most common first-call failure on a new account.
- Balances are shared with the REST API and the website. One Cloud Request is one new
transcript; frame analysis spends 1 Cloud Request plus AI Units, and audio transcription spends
AI Units on top of its Cloud Request. A run refused before it
starts costs nothing, and
analyze_video with estimateOnly: true quotes the price for free.
- Rate limit per minute, by plan: Free 60, Starter 200, Pro 500, Team 1,000 requests. The
server is stateless, so a client re-runs
initialize before every call and one tool call is
several requests. analyze_video has 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.
GET and DELETE return a JSON-RPC error rather than an HTML 404.
- No captions, or the wrong ones. For a video with no caption track, pass
transcribeAudio: true to transcribe it from the audio; to replace captions that exist (all
uploaded translations, say), pass source: "audio". Both are paid features, priced per minute
of video, and never run without being asked for.
Full numbers: pricing.
Prompts
The server also publishes three prompts, which clients such as Claude show as ready-made actions.
Each tells the model which tools to use and in what order, cheapest first.
| Prompt | Arguments | What it does |
|---|
summarize_video | video | A timestamped summary of one video, read the cheapest way available. |
research_channel | channel, topic | What a channel has said about a topic, with cited moments. |
find_in_my_library | topic | Searches everything already saved — free. |
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
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.