MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Description from the maker (original English)
Competitive intelligence for agents: competitor teardowns, pricing, ads, reviews and momentum.
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.
RIVALIZE_API_KEY, RIVALIZE_API_URL, RIVALIZE_MCP_ALLOW_WRITESValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"rivalize": {
"command": "npx",
"args": [
"-y",
"@rivalize/mcp"
],
"env": {
"RIVALIZE_API_KEY": "your-value",
"RIVALIZE_API_URL": "your-value",
"RIVALIZE_MCP_ALLOW_WRITES": "your-value"
}
}
}
}Run this in your terminal
claude mcp add rivalize --env RIVALIZE_API_KEY=your-value --env RIVALIZE_API_URL=your-value --env RIVALIZE_MCP_ALLOW_WRITES=your-value -- npx -y @rivalize/mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"rivalize": {
"command": "npx",
"args": [
"-y",
"@rivalize/mcp"
],
"env": {
"RIVALIZE_API_KEY": "your-value",
"RIVALIZE_API_URL": "your-value",
"RIVALIZE_MCP_ALLOW_WRITES": "your-value"
}
}
}
}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": {
"rivalize": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@rivalize/mcp"
],
"env": {
"RIVALIZE_API_KEY": "your-value",
"RIVALIZE_API_URL": "your-value",
"RIVALIZE_MCP_ALLOW_WRITES": "your-value"
}
}
}
}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.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
RIVALIZE_API_URL envRIVALIZE_MCP_ALLOW_WRITES envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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 rivalize.ai (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
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.
You need to fill in: RIVALIZE_API_KEY
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.3.2) reached the registry 27 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
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.
@rivalize/mcp)Give Claude, Cursor, Cline, or your own agent cited competitor intelligence as JSON, over the Model Context Protocol.
The Agent plan ($70 a year or $9 a month): API and MCP only, for your own AI. Rivalize collects; your own Claude, Cursor or agent does the thinking. No dashboard and no AI analysis, so it costs a few dollars.
list_universe_companies, get_universe_company)Get the Agent plan at rivalize.ai/pricing. Developer and API documentation: rivalize.ai/developers.
This server connects Claude, Cursor or any other MCP client to Rivalize. Your assistant can tear down a competitor's positioning, pricing, ads, social presence, reviews, hiring and momentum in one call, search the Rivalize universe of tracked companies, and read the projects, reports, battlecards, timelines and evidence in your own Rivalize account. Every answer comes from data Rivalize has collected, with dates and sources, rather than from a model's memory.
The server is read-only by default. Three write tools, add_competitor, run_report and set_agent_competitor, are available when you opt in with RIVALIZE_MCP_ALLOW_WRITES=1. run_report starts a real report that uses your credits, so it asks you to preview first and confirm.
Requires Node.js 22 or newer (node --version).
rk_live_. A key from any plan works, including the free plan, which gets rate-limited reads.Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows), then restart Claude Desktop:
{
"mcpServers": { "rivalize": { "command": "npx", "args": ["-y", "@rivalize/mcp"], "env": { "RIVALIZE_API_KEY": "rk_live_..." } } } }
claude mcp add rivalize -e RIVALIZE_API_KEY=rk_live_... -- npx -y @rivalize/mcp
Add to .cursor/mcp.json in your project, or ~/.cursor/mcp.json for all projects:
{
"mcpServers": { "rivalize": { "command": "npx", "args": ["-y", "@rivalize/mcp"], "env": { "RIVALIZE_API_KEY": "rk_live_..." } } } }
In Cline, open the MCP Servers panel, choose Configure, then Configure MCP Servers. This opens cline_mcp_settings.json. Add:
{
"mcpServers": { "rivalize": { "command": "npx", "args": ["-y", "@rivalize/mcp"], "env": { "RIVALIZE_API_KEY": "rk_live_..." } } } }
Save the file. The rivalize server appears with a green dot after about 10 to 15 seconds (the first start downloads the package). On Windows, if it does not start, use "command": "cmd" and "args": ["/c", "npx", "-y", "@rivalize/mcp"].
If you ask Cline to install it for you, point it at llms-install.md.
The server speaks MCP over stdin and stdout. Configure your client to launch:
| Setting | Value |
|---|---|
| Command | npx |
| Arguments | -y @rivalize/mcp |
| Environment | RIVALIZE_API_KEY=rk_live_... |
| Transport | stdio |
On Windows, some clients cannot launch npx directly because it is npx.cmd. Use cmd as the command and /c npx -y @rivalize/mcp as the arguments instead.
| Plan | Price | Competitors | What is included for MCP and API |
|---|---|---|---|
| Agent | $70/yr or $9/mo | 3 at once, refreshed every 7 days | API and MCP only, for your own AI. Everything Rivalize collects about each competitor as JSON, access to Rivalize's database of companies already collected, and 500 API and MCP calls a day (250 an hour). One competitor change per slot per calendar month. No dashboard and no AI analysis. |
| Starter | $19/mo ($190/yr) | 3 | Web dashboard, Monday briefing, cited change alerts, plus API, MCP and webhooks. |
| Growth | $79/mo ($790/yr) | 10 | Everything in Starter with broader coverage, plus recommended actions on material changes. |
| Pro | $199/mo ($1,990/yr) | 25 | Everything in Growth plus cited sales battlecards (get_battlecard) and 1-year change history. |
| Agency | $599/mo ($5,990/yr) | 50 | Unlimited client workspaces, dashboard, battlecards, webhooks, plus API and MCP. |
Prices and limits are always current at rivalize.ai/pricing.
Sixteen read-only tools are always available: fourteen for dashboard plans and two for Agent plans. The three write tools (add_competitor, run_report and set_agent_competitor) are registered only when RIVALIZE_MCP_ALLOW_WRITES is set to 1, true or yes; without it, they do not exist for the client.
| Tool | Access | What it does | Key arguments |
|---|---|---|---|
teardown_competitor | read | One-call strategy teardown of a competitor as Markdown: positioning, pricing, ads, social, reviews, hiring, momentum and weaknesses to attack, with when the data was last refreshed | domain (required) |
list_universe_companies | read | Search the Rivalize universe, the cross-customer dataset of tracked companies | q, category (slug), layer, limit (1-100), offset |
get_universe_company | read | Full universe profile for one company: identity, pricing, features, ads, social, reviews, funding and hiring, rankings, signals, momentum | domain (required), layers |
list_projects | read | The projects in your account; returns the project_id other tools take | none |
list_reports | read | Your reports, newest first. Reading never generates a report | project_id, limit (1-100), offset |
get_report | read | One report as Markdown, whole or one section or one competitor at a time | report_id (required), section, competitor, page |
list_competitors | read | The competitors you track, with momentum score, its threat-level band and, where the API provides it, each rival's standing on your Brief | project_id, limit (1-100), offset |
get_competitor_intelligence | read | Latest stored intelligence for one tracked competitor; a field is present only when it was measured | competitor_id (required) |
get_battlecard | read | Cited sales battlecard for one tracked competitor. Requires a Pro plan | competitor_id (required) |
get_strategic_timeline | read | Evidence-linked timeline of competitor moves across pricing, product, people, funding and content/social | project_id (required), days (30, 90, 180), competitor_id, lanes, format, page |
get_competitive_landscape | read | Current or stored weekly positions of competitors by activity and strategic importance | project_id (required), week (YYYY-MM-DD), format, page |
get_freshness | read | When each tracked competitor in a project was last actually observed, and how | project_id (required) |
get_evidence | read | The sources behind the facts for your product or one competitor: URL, what it supports, and when it was read | project_id (required), competitor_id |
add_competitor | write, opt-in | Add competitor URLs to a project. Spends credits and queues analysis | project_id (required), urls (1-10, required) |
run_report | write, opt-in | Starts a real report that uses your credits (paid dashboard plans; about 10 to 20 minutes). Two steps: without confirm it starts nothing and returns a preview (depth, the project's competitors, the credits it will use, credits and monthly reports left, expected time). With confirm: true it starts the run. depth is full (15 credits per 5 competitors, uses a monthly report) or quick (1 credit per competitor). At most 3 runs a day through the API or MCP per account, and the same request within 10 minutes returns the run already started | project_id (required), depth, confirm |
get_report_status | read | Whether a report started with run_report has finished (processing, completed, no_competitors, no_rivals), and the next call. Poll no more often than every 30 seconds | report_id (required) |
list_agent_competitors | read | Agent plans. The 3 tracked-competitor slots: who is tracked, when each was last collected, when it refreshes next (every 7 days), and how many slot changes are left this calendar month | none |
get_agent_competitor | read | Agent plans. The raw data collected about one tracked competitor, by group (core, ads_seo, extended), each module with its source and collected_at. A group your plan does not include is listed under not_in_plan. Your own assistant does the analysis | competitor_id (the domain, required), group |
set_agent_competitor | write, opt-in | Agent plans. Put a competitor in a slot, or replace the one in a slot (slot 0-2). Uses no credits and queues a collection. Each slot can be replaced once per calendar month (the refusal gives the reset date); a fourth competitor at once is refused | url (required), name, slot |
Agent plans cannot run work that needs a model (battlecards, teardown prose, reports): the API refuses those calls with an agent_* code and the tool shows you the API's sentence unchanged. run_report and the dashboard reads are for dashboard plans; the Free and Agent plans are refused by the API with PLAN_REQUIRED or agent_model_work_not_in_plan.
project_id and competitor_id are UUIDs from list_projects and list_competitors. Tools that read your account only ever see your own data.
get_report takes a section so your assistant can read the part a question needs instead of the whole report:
| Section | Contains |
|---|---|
tldr, biggest-threat, blind-spots, actions | The report's headline sections (actions is what your product should do) |
battlecards | The cited sales battlecards |
competitors | Every competitor's section in full |
pricing, momentum, app-store, strengths, weaknesses, key-findings, creators, ads, tech-stack | One topic gathered from every competitor's section |
A report has only the sections it has data for; asking for any other name returns an error that lists the sections it does have. section combines with competitor, so section: "pricing" with competitor: "Acme" returns Acme's pricing. A figure the report's fabrication check could not match to a source is kept and marked (not confirmed in the pages read); a name or citation the check found to belong to another entity is taken out with its sentence, exactly as in the report.
Every response stays under 25,000 characters, and nothing is cut silently:
get_report, get_strategic_timeline, get_competitive_landscape) is split into pages at section boundaries. Each page starts with Page N of M, how much remains, and the exact call for the next page.Only the beginning is shown; read the rest in the repo