@vivideo/mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@@vivideo/mcpcreate a 20-second product teaser with text 'Spring Sale'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Vivideo Toolchain
The developer + agent integration layer for the Vivideo API — a shared client, an MCP server, a CLI, and Skills. Agents are a primary user, not an afterthought.
Everything sits on top of the public API (the source of truth). No backend business logic is duplicated here — the toolchain only adds client-side ergonomics and guardrails.
vivideo-toolchain/ npm workspaces monorepo (TypeScript)
├── packages/core @vivideo/core one typed API client + guardrails (shared)
├── packages/mcp @vivideo/mcp MCP server (stdio) — 13 agent tools
├── packages/cli @vivideo/cli `vivideo` CLI — humans, scripts, CI, agents
├── skills/ reusable agent Skills (SKILL.md)
└── docs/ installation, configuration, workflowsArchitecture
One client, one set of types, derived from packages/core/openapi.yaml. The MCP server and CLI both call @vivideo/core — there is exactly one representation of each request/response, so the tools, CLI, docs and OpenAPI stay consistent.
@vivideo/core adds only client-side concerns, never business logic:
Guardrail | What it does |
Rate limiting | Token-bucket cap on request rate (default 8/s) — the client can't become a request flood. |
Concurrency cap | Semaphore limits in-flight requests (default 4). |
Bounded retries | Retries only |
Honors | On 429 it waits the API-specified delay before retrying. |
Idempotency | Every video-create sends an |
Timeouts | Per-request |
Safe waiting |
|
Secret redaction | API keys / signing secrets are stripped from every log, error, and output. |
These complement — and never bypass — the API's own auth, rate limits, idempotency, credit checks, premium gates, ownership and error model.
Related MCP server: Vimeo MCP Server
Quick start
# from the repo (until packages are published to npm)
npm install
npm run build
# authenticate (stored 0600 in ~/.vivideo/config.json), or use VIVIDEO_API_KEY
export VIVIDEO_API_KEY="vv_live_..." # from https://app.vivideo.ai/account/api-keys
# CLI
node packages/cli/dist/index.js account
node packages/cli/dist/index.js create auto --prompt "A 20s product teaser" --wait
# MCP server (stdio) — point an MCP client at this command
node packages/mcp/dist/index.jsOnce published: npm i -g @vivideo/cli (gives vivideo), and npx @vivideo/mcp for the server.
Docs
MCP server — install, configure, connect to clients, tool reference
CLI — install, auth, command reference, JSON & non-interactive use, exit codes
Security, rate limits, idempotency, credits & premium, troubleshooting
Authentication & security
Keys are read from (in order): explicit option →
VIVIDEO_API_KEYenv →~/.vivideo/config.json(written owner-only0600).The key is never printed — all output passes through secret redaction;
configurestores it without echoing it.Keys are account-scoped secrets. Keep them server-side; one per integration so a leak is revocable in isolation.
Not included (honest scope)
Cancellation — the public API has no cancel endpoint, so no cancel tool/command is offered. Failed/stuck renders are auto-refunded by the API.
Agent/chat mode — not exposed by the public API, so not in the toolchain.
Nothing here publishes to npm, provisions DNS, or deploys — those are external steps (see the final section of docs/mcp.md).
Development
npm run build # build all three packages (tsc -b)
npm run typecheck # type-check the whole workspace
npm test # vitestRequires Node ≥ 18.17.
This server cannot be deployed
Maintenance
Related MCP Connectors
MCP server for Clipkit — gives AI agents a video toolbox via the Clipkit schema.
MCP server for Google Veo AI video generation
MCP server for your apps' tools and custom tools, plus hosted AI agents and approval-gated workflows
Build, run, schedule, and publish AI video pipelines to YouTube and TikTok from any MCP client.
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