Quiz.Video MCP

Live

OAUTH 2.1

VIDEO GENERATION

Media

Quiz.Video MCP gives agents authenticated access to quiz video generation: create quizzes, add questions, queue a render, and download the finished MP4.

  • Per-user credentials: each call uses the actual user's token, never a shared bot.
  • Encrypted per-tenant vault: AES-256, resolved at request time, never in LLM context.
  • Scoped before every call: pre-call scope check, 90-day SIEM-exportable audit chain.
Quiz.Video MCP
agent · Acme Q3
Run
Generate a 10-question trivia quiz about 90s movies and render it.
S
quizvideomcp_quiz_video_generate_quiz
189ms
Quiz.Video agent
Quiz created with 10 questions. Render queued, session rnd_7712, ready in about 2 minutes.
Sources: 1 quiz, 1 render
quizvideomcp
1 quiz
18:29
Message Claude...

Tools your content agent reaches for on Quiz.Video, scoped per user.

CALL ANY TOOL
Generate quiz videos end to end: create or AI-generate a quiz, queue the render, and download the finished video, scoped to each user's own account.
quizvideomcp_quiz_video_generate_quiz
Generate quiz
AI-generate and save a quiz from a topic, with an optional custom visual theme and auto-render.
Parameters
Name
Type
Required
Description
topic
string
Required
Subject the AI should build the quiz around.
autoRender
boolean
Optional
If true, immediately queue a video render for the new quiz.
answerOptionCount
number
Optional
Answer options per question for multiple-choice quizzes. Defaults to 4.
quizvideomcp_quiz_video_create_quiz
Create quiz
quizvideomcp_quiz_video_add_quiz_questions
Add quiz questions
quizvideomcp_quiz_video_create_render
Create render
quizvideomcp_quiz_video_get_render
Get render
quizvideomcp_quiz_video_download_render
Download render
Build your Agent
Same auth pattern across LangChain, OpenAI, Anthropic, and Google ADK.
Python · LlamaIndex
import { ScalekitClient } from "@scalekit-sdk/node";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

// Quiz.Video tools scoped to this user
const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["quizvideomcp"], toolNames: [
    "quizvideomcp_quiz_video_generate_quiz",
    "quizvideomcp_quiz_video_create_quiz",
    "quizvideomcp_quiz_video_add_quiz_questions"] },
  pageSize: 100,
});

const agent = createReactAgent({ llm, tools });
await agent.invoke({ messages: [{ role: "user", content: "Generate a 10-question trivia quiz about 90s movies and render it" }] });
import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["quizvideomcp"] }, pageSize: 100,
});

const res = await openai.chat.completions.create({
  model: "gpt-5",
  messages: [{ role: "user", content: "Generate a 10-question trivia quiz about 90s movies and render it" }],
  tools,
});

// Execute the tool call with the user's vaulted quizvideomcp credential
await sk.tools.executeTool(res.choices[0].message.tool_calls[0], "user_123");
import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["quizvideomcp"] }, pageSize: 100,
});

const msg = await anthropic.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Generate a 10-question trivia quiz about 90s movies and render it" }],
  tools,
});

// Tool call runs with the user's vaulted quizvideomcp credential
await sk.tools.executeTool(msg.content, "user_123");
import { Agent } from "@google/adk/agents";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["quizvideomcp"] }, pageSize: 100,
});

const agent = new Agent({
  name: "quizvideomcp_agent",
  model: "gemini-2.5-pro",
  instruction: "Quiz.Video tools scoped to this user",
  tools,
});

await agent.run("Generate a 10-question trivia quiz about 90s movies and render it");
Try these prompts
Copy any prompt into your agent. Each maps directly to a Quiz.Video MCP tool. Click to copy, paste into your agent, done.
Generate a quiz
Copy the prompt
Copied
Generate a 10-question trivia quiz about 90s movies.
Copy the prompt
Copied
Create a picture-guess quiz about world flags, TikTok format.
Copy the prompt
Copied
Add 3 more questions to quiz qz_88x21m.
Render and download
Copy the prompt
Copied
Queue a render for quiz qz_88x21m.
Copy the prompt
Copied
Check the render status for session rnd_7712.
Copy the prompt
Copied
Get the download URL for the completed render rnd_7712.
Templates and flashcards
Copy the prompt
Copied
List available visual templates for quizzes.
Copy the prompt
Copied
Apply the neon template to my last 3 quizzes.
Copy the prompt
Copied
Create a flashcard deck for Spanish vocabulary, 20 cards.
SEE HOW AUTH WORKS
Your users connect once. Their Quiz.Video MCP credentials stay vaulted, every call is checked, and every action is logged.
1
Authorize
Your user connects
Quiz.Video MCP
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
Quiz.Video MCP
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
Quiz.Video MCP
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
Quiz.Video MCP
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
See the same per-user auth pattern across other media and content-generation connectors.
GTM
HubSpot to Slack updates agent
Watch HubSpot deal stage changes and post structured updates to the right Slack channel. Reps stop checking the CRM all day.
SALES
Deal intelligence agent
Combine Gong, Attio, and Slack signals to surface deal risks and next-best actions. Updated after every call.
GTM
CRM AI agent
Log calls, update opportunity stages, and surface stalled deals across HubSpot or Salesforce. No manual data entry.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
Other connector libraries treat auth as a demo afterthought. Scalekit starts with identity, scope enforcement, and audit. Connectors follow.
01.
Shared tokens break per-user analytics
A shared Quiz.Video MCP token looks fine in a demo. In production every quiz render looks like one service account, and you cannot tell which user triggered it. Scalekit resolves the credential of the actual user who triggered the agent, never a shared bot.
// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
Quiz.Video MCP today. Ten connectors tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions
Does the agent access Quiz.Video MCP as the user or through a shared key?
As the user. Scalekit resolves the credential of the person who triggered the agent at request time, so every Quiz.Video MCP action in your audit trail is attributed to a real user, not a shared service account.
Where is the Quiz.Video MCP token stored?
In an AES-256 encrypted vault with per-tenant namespacing. Tokens are resolved at request time, never enter LLM context, refresh automatically, and can be revoked from one dashboard.
Can I limit what the agent does in Quiz.Video MCP?
Yes. Filter by tool name in listScopedTools to expose only what you want. Scalekit also enforces scope checks before every API call.
What happens when a user revokes access?
The credential is invalidated at the next tool call. The call fails closed, other users' connections are unaffected, and the revocation is logged in the audit chain.
Can the agent publish a quiz publicly without the user reviewing it?
The quiz page is viewable at its watch URL as soon as it's created, so scope generate_quiz carefully if you want a review step. Keep create_render and download_render available for drafts while gating public distribution outside the agent.
Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""quizvideomcp"": {
""url"": ""https://mcp.scalekit.com/quizvideomcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.quizvideomcp]
url = ""https://mcp.scalekit.com/quizvideomcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""quizvideomcp"": {
""url"": ""https://mcp.scalekit.com/quizvideomcp"",
""type"": ""http""
}
}
}