Power your agent
คำสั่งของผู้เผยแพร่เอง ไม่ใช่เอนด์พอยต์ของ PlugMCP
Host a copy with our keys and logs.
npx -y [email protected]Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
claude mcp add cueframe -- npx -y cueframe@0.12.1รันในเทอร์มินัล
{ "mcpServers": { "cueframe": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}claude_desktop_config.json
URL แบบรีโมตหรือคำสั่งบนเครื่องของคุณ? การติดตั้งสองแบบต่างกันอย่างไร
รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดจากผู้เผยแพร่
CueFrame is a hosted service for composing, editing and rendering video. Connect your agent over MCP, automate an edit from the CLI, or integrate the REST API into your application. Each surface works with editable projects containing clips, captions and motion graphics, and renders them to MP4.
CueFrame video editing CLI: manage media, edit compositions and render MP4s from terminals and scripts.
A frame from the Yosemite Peregrines template. Watch the video and try the same edit.
For Claude Code, Codex, Cursor, VS Code, and other supported local agents, run this in your terminal with Node.js 24 or newer:
npx -y [email protected] install
The installer detects supported agents and adds the hosted CueFrame MCP endpoint to their configuration. It installs the skills in ~/.agents/skills and ~/.claude/skills, preserving locally modified skills by default. It can update multiple detected clients; use --dry-run to inspect the changes first.
Restart your agent session. Then ask:
Use CueFrame's get_account tool to check my connection and show my available credits.
Your client may prompt you to authenticate or open a browser. Sign in to CueFrame and authorize the connection; interactive OAuth clients need no API key. Cloud operations use credits. Check your balance and estimated costs before starting paid work; see cloud rates.
ChatGPT and Claude Desktop: use your client's hosted connector setup with https://api.cueframe.ai/v1/mcp, then authenticate. The terminal installer does not configure ChatGPT. See the connection guide and CueFrame connection skill for supported paths. Skills installation and hosted connector setup are separate steps.
Already connected? Skip installation and give your agent a video task. If CueFrame's tools do not appear, restart the client and check its MCP connection settings.
Try the Yosemite first-render walkthrough: render a template, change one word, and render again from the same project.
Download the full original footage from the National Park Service as yosemite-peregrines.mp4. Use the original source, because the finished demo has its title baked in. Follow the source's download and reuse guidance.
Give your connected agent the source file and this instruction:
Use CueFrame to start the yosemite-peregrines template from cueframe-ai/cueframe-templates with this original video. Load template.cueframe and its prepared subject matte. Preview the editable project and estimate cloud costs. After I approve the render, return the MP4 link and project ID.
After the first render, ask:
In that same project, replace the behind-subject title PHENOMENAL with EXTRAORDINARY. Preserve the footage, spoken captions, audio, timing, placement, and depth. Preview the changed title, estimate the render cost, and render after I approve.
The template selects 83.616–93.359 seconds of the original video. You should get two MP4s from one editable project. Uploading footage and running cloud operations use credits; the two renders are billed separately.
The project stays editable: the desktop editor shows the title as a separate layer, alongside footage and captions. Watch the title change.
flowchart LR
A[Your request + footage] --> B[Your agent + CueFrame skills]
B --> C[Hosted CueFrame MCP]
C --> D[Editable project + preview]
D --> E[Render job → MP4 link]
The agent inspects available tools, checks your account, prepares media and the project, previews changes, and submits a render. Long-running operations return IDs; the agent waits for completion and gives you the result. You do not need to write the tool calls yourself. The detailed quickstart explains the individual calls.
For your next video, describe the result and provide the inputs:
Turn this interview into a 20-second vertical clip with word-timed captions. Preview the strongest moment and show estimated costs before rendering.
Find an image-carousel component for these product photos. Show suitable choices and their required inputs before creating the video.
Change only the final title in this project. Keep the rest of the edit unchanged.
Choose one setup path. A plugin installs the skills and hosted MCP configuration together. A server-only connection adds tools; skills provide the workflow guidance.
Claude Code:
claude plugin marketplace add cueframe-ai/cueframe-mcp
claude plugin install cueframe@cueframe
Codex:
codex plugin marketplace add cueframe-ai/cueframe-mcp
codex plugin add cueframe@cueframe
Restart the session, authenticate when prompted, and ask the agent to call get_account.
Gemini CLI:
gemini extensions install https://github.com/cueframe-ai/cueframe-mcp
Install skills in any client that supports Agent Skills:
npx skills add cueframe-ai/cueframe-mcp
Skills alone do not connect the MCP server. Add the hosted endpoint through your client's MCP settings if it is not already connected.
The hosted endpoint is https://api.cueframe.ai/v1/mcp, using Streamable HTTP. For example, in Claude Code:
claude mcp add --transport http cueframe https://api.cueframe.ai/v1/mcp
For Cursor and VS Code, use the one-click links in the connection guide. Configuration keys differ between clients. Per-client examples are in examples/.
Interactive clients can use browser sign-in. Headless clients send Authorization: Bearer cf_live_…; see llms-install.md for authentication and stdio bridge options. The glama/ shim executes no tools and cannot be used to make videos.
Skills teach the agent how to carry out video tasks. You describe the task; the agent selects the relevant guidance.
Claude Code's session hook and Cursor's rule help select the entry point. Other hosts load the installed skills through their own mechanisms. Scoped edits should preserve unrelated work.
Use the CLI for explicit video commands, shell scripts and structured JSON output. It connects to the hosted API; it does not run a local renderer. Requires Node.js 24 or newer.
npx -y [email protected] --help
npx -y [email protected] login
npx -y [email protected] api GET /v1/me --json
npx -y [email protected] describe --json
login opens the browser to authenticate. Headless scripts can supply CUEFRAME_API_KEY. The account request checks your connection and credits; describe lists command arguments and options without making an API call.
Use the REST API to create projects, import media, change compositions and follow render jobs from your application. Requests go to https://api.cueframe.ai with an API key from your account. Check your account before metered operations; cloud rendering and processing use credits.
For TypeScript or JavaScript on Node.js 24+, install the typed client:
npm install @cueframe/sdk
import { account, createClient } from "@cueframe/sdk";
if (!process.env.CUEFRAME_API_KEY) throw new Error("Set CUEFRAME_API_KEY");
createClient({
baseUrl: "https://api.cueframe.ai",
apiKey: process.env.CUEFRAME_API_KEY,
});
const result = await account.getAccount();
console.log(result.plan, result.entitlements);
Other languages can call REST directly or generate a client from the versioned public OpenAPI contract. The SDK is a client for the hosted service, not the server implementation.
This repository contains the agent plugin, developer toolkit, and registry files. The hosted MCP server is maintained separately in the application repository. You connect to CueFrame's hosted service; cloning this repository does not run that service locally.
Documentation, client examples, skill improvements, and toolkit fixes are welcome. Start with good first issues or read CONTRIBUTING.md for setup, generated-file rules, tests, and commit sign-off.
Edit skills in root skills/; change generated API clients through their documented inputs. Report hosted-service problems in this repository's issue tracker with reproduction steps and a request ID when available. Report vulnerabilities privately using SECURITY.md. Community participation follows the Code of Conduct.
The MCP server itself (@cueframe/mcp) is a private package maintained in the application repository; this repository ships the contract it is generated from, the clients, the plugin, the registry entry (server.json) and a discovery shim, not the server.
private API ──sync──▶ api/openapi.json (+ scene-schema.json, scene-examples.json, contract-manifest.json)
│
├──▶ packages/api-contract/dist ──publish──▶ @cueframe/[email protected] ──▶ the MCP server's generators, third parties
└──▶ packages/sdk/src/generated (Orval: operations, models, zod)
The private API publishes its OpenAPI projection into api/; pnpm generate:api-consumers regenerates the SDK from it. This is the one copy of the contract: the MCP server's generators in the application repository and every other consumer read it from the @cueframe/api-contract npm package, whose version moves with the contract (pnpm check:contract-version fails an api/*.json change without a bump), so the tool surface and the SDK always describe one contract. Nothing under api/ or a generated/ directory is hand-edited: pnpm check:api-inputs proves the three api/*.json inputs came from one sync, and pnpm check:api-consumer-drift proves the generated trees match them byte for byte.
Root skills/ is the single source: the plugin hosts read it from this repository, and pnpm build copies it into packages/skills/dist (published as @cueframe/skills) and from there into the CLI's dist/skills for cueframe install. pnpm check:plugin validates every skill and manifest; agents/openai.yaml and assets/icon.svg beside each skill are generated.
server.json: the MCP registry entry for the hosted server (ai.cueframe/cueframe, remotes only). pnpm check:server-json validates it against the vendored registry schema; the registry job of the publish workflow publishes it.glama.json: the Glama listing's maintainer file.glama/ and the Dockerfile: a stdio discovery shim that replays a snapshot of the hosted server's tool list and instructions for registries that introspect over stdio. It is not a server (see below).The hosted service, desktop integration, and registry shim serve different purposes.
https://api.cueframe.ai/v1/mcp is the product. Every install line above talks to it; it authenticates with OAuth or an API key and does the composing and rendering. Its package, @cueframe/mcp, is private.cueframe-mcp; it lives inside the app bundle.glama/server.mjs, built by the Dockerfile) is not a server. It replays a snapshot of the hosted server's tool list and instructions over stdio so registries that build an image can list the tools without an account; every tools/call answers with a pointer to the hosted server. glama/refresh-snapshot.md says where the snapshot comes from.skills/<name>/SKILL.md: the skill. agents/openai.yaml and assets/icon.svg beside it are generated (pnpm build:plugin)..claude-plugin/, hooks/, .mcp.json: Claude Code plugin, session router and server..codex-plugin/, .agents/plugins/, mcp.json: Codex and ChatGPT plugin and marketplace..cursor-plugin/, rules/: Cursor plugin and the always-on rule.gemini-extension.json, skills.sh.json, plugin.json: Gemini CLI, skills.sh, the portable manifest (agent-plugins.org).api/, packages/, tools/, scripts/: the contract, the four npm packages, their generators and checks (scripts/plugin/ holds the plugin's).server.json, glama.json, glama/, Dockerfile: the registry files.catalog/: the tool reference and error codes exported from the MCP catalog in cueframe-ai/cueframe (pnpm --filter @cueframe/mcp export:tool-reference -- <this repository>/catalog there). skills/cueframe-connect/references/tools.md is rendered from it, and the skills check reads it: a skill may name only a tool it lists.examples/, llms-install.md: per-client setup and the agent-readable install guide.pnpm install
pnpm check # input provenance, the contract version rule, the public-contract gate, server.json, the plugin, and tsc --noEmit in sdk and cli
pnpm build # stamps the plugin manifests and skill cards, then tsup in every package; the CLI packages the skills
pnpm test
Node 24 or newer and pnpm (see .nvmrc and packageManager). CONTRIBUTING.md explains which paths are generated, the skill contract and how a change travels; AGENTS.md is the same for an agent working in this tree; llms-install.md connects a client step by step.
CueFrame video editing CLI: manage media, edit compositions and render MP4s from terminals and scripts.
{ "mcpServers": { "cueframe": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
Cueframe ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-11 CueFrame video editing CLI: manage media, edit compositions and render MP4s from terminals and scripts.