MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Description from the maker (original English)
Telegram-native CRM for agents: contacts, deals, projects, tasks, campaigns, docs and reports.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Works in Claude on the web, desktop and mobile:
https://ai.cavyro.com/mcpRun this in your terminal
claude mcp add --transport http cavyro https://ai.cavyro.com/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"cavyro": {
"url": "https://ai.cavyro.com/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"cavyro": {
"type": "http",
"url": "https://ai.cavyro.com/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
https://ai.cavyro.com/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
We have not read this server’s tool list yet; we check endpoints in rotation.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified against the domain cavyro.com (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
Not checked yet; we check endpoints in rotation
Not checked yet; we check endpoints in rotation
Not checked yet; we read the tool list when we check the endpoint
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (1.1.0) reached the registry 6 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Cavyro is a Telegram-native CRM for agents and small sales teams: contacts, companies, deals, pipelines, projects and tasks, campaigns, docs and reports. This repository describes Cavyro's hosted Model Context Protocol server, listed in the MCP Registry as com.cavyro/cavyro.
The server is hosted, so there is nothing to install or run. Point your MCP client at it and it reads and acts on your Cavyro workspace with your permissions.
https://ai.cavyro.com/mcp (Streamable HTTP)https://ai.cavyro.com/.well-known/mcp/server-card.json (full tool surface with input schemas, no credentials needed)server.json · Changes: CHANGELOG.mdThe server source is not published here. The tool surface is generated from the running server and exposed in the server card above, so the card is always the authoritative description of what the server does.
The server exposes a fixed set of nine generic tools over a resource and action registry, instead of one tool per API operation. The client discovers resources and actions on demand, so the tool list stays small while covering over 200 operations across 24 resources.
| Tool | Purpose |
|---|---|
describe_resource | Catalog of all resources and global actions, or one resource's filters, sort fields, enums, operations and actions |
query_resources | List records of any resource with filters, sort, pagination and custom-field filters |
get_resource | Fetch one record by ID |
create_resource | Create a record (custom fields nested under custom_fields) |
update_resource | Change fields on a record |
delete_resource | discard (archive), restore, or destroy a record |
search | Omnibox search across entity types |
perform_action | Any specialized non-CRUD action by slug: move a deal between stages, link records, bulk operations, comments, reports |
load_guidance | On-demand workflow guidance: create flows, custom fields, automations |
Covered domains: deals, contacts, companies, pipelines and stages, projects with folders, task lists, tasks and subtasks, project reports, comments and reactions, activity feed, notifications, a personal My Work queue with mentions, workspaces, members, teams, groups, invitations, custom field definitions, automations, docs with their pages, reports, Google Calendar meetings, read-only Telegram chats and Telegram follow-up reminders.
All tool responses share one envelope, { "data": ..., "pagination": ... }, with pagination present only on paginated list results.
The connection acts as you. An external AI can only see and do what your Cavyro role allows in that workspace.
Every request needs two headers:
| Header | Value |
|---|---|
Authorization | Bearer |
X-Workspace-Id | Your workspace ID |
Create an API token in Cavyro under Settings → API tokens. Tokens can expire after 7, 30 or 90 days, or never for integrations that cannot rotate them. Revoking a token cuts the client off immediately.
There is no OAuth flow. The server answers unauthenticated requests with 401 and a WWW-Authenticate: Bearer realm="cavyro" challenge. MCP is a Pro feature; MCP calls do not consume Cavyro AI credits, the model tokens are paid by your own client subscription.
Replace and in the snippets below. Cavyro's settings page generates the same snippet with your workspace ID filled in.
.vscode/mcp.json, or MCP: Add Server from the command palette:
{
"servers": { "cavyro": { "type": "http", "url": "https://ai.cavyro.com/mcp", "headers": { "Authorization": "Bearer ${input:cavyro-token}", "X-Workspace-Id": "${input:cavyro-workspace}" } } }, "inputs": [ { "id": "cavyro-token", "type": "promptString", "description": "Cavyro API token", "password": true }, { "id": "cavyro-workspace", "type": "promptString", "description": "Cavyro workspace ID" } ] }
The Add to Cursor button above installs the server with placeholder headers; replace them in ~/.cursor/mcp.json.
Cursor: ~/.cursor/mcp.json. Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json.
{
"mcpServers": { "cavyro": { "url": "https://ai.cavyro.com/mcp", "headers": { "Authorization": "Bearer ", "X-Workspace-Id": " " } } } }
claude mcp add --transport http cavyro https://ai.cavyro.com/mcp \
--header "Authorization: Bearer " \ --header "X-Workspace-Id: "
Add the server as a connector in Developer Mode (Plus, Pro, Business or Enterprise) with the URL https://ai.cavyro.com/mcp and the two headers above.
Once connected, ask your assistant in plain language. A few things that work well:
The assistant will typically call describe_resource first to learn the shape of a resource, then query_resources or perform_action. If it needs a multi-step recipe, it calls load_guidance.