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Rendobar

作者:rendobar版本 1.13.0i★ –i电脑或云端
注册名称com.rendobar/mcp

安装

概览

作者提供的说明(英文原文)

Transform video, audio and images, and generate media from prompts. FFmpeg, captions, models.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 电脑或云端
  • 传输方式: stdio, Streamable HTTP
  • 分类: 设计、图片与音频
  • 你需要填写:RENDOBAR_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • 在云端运行无需安装任何东西,通过互联网连接
  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://api.rendobar.com/mcp

或者在你的电脑上运行

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "rendobar": {
      "command": "npx",
      "args": [
        "-y",
        "@rendobar/mcp"
      ],
      "env": {
        "RENDOBAR_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add --transport http rendobar https://api.rendobar.com/mcp

或者在你的电脑上运行

claude mcp add rendobar --env RENDOBAR_API_KEY=your-value -- npx -y @rendobar/mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "rendobar": {
      "url": "https://api.rendobar.com/mcp"
    }
  }
}

或者在你的电脑上运行

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "rendobar": {
      "command": "npx",
      "args": [
        "-y",
        "@rendobar/mcp"
      ],
      "env": {
        "RENDOBAR_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "rendobar": {
      "type": "http",
      "url": "https://api.rendobar.com/mcp"
    }
  }
}

或者在你的电脑上运行

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "rendobar": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@rendobar/mcp"
      ],
      "env": {
        "RENDOBAR_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://api.rendobar.com/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • RENDOBAR_API_KEY 机密 env
    Rendobar API key (starts with 'rb_'). Get one at https://app.rendobar.com/settings/api-keys. The server starts without it so tools can be listed, but tool calls require it.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 rendobar.com 验证(注册中心会核实域名所有权)

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“设计、图片与音频”中的其他服务器比较i

  • 星标数多于此分类中其他 2166 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2166 个服务器的 52% 更新
  • 基础检查结果等于或优于此分类中其他 2166 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Rendobar 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:RENDOBAR_API_KEY

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.13.0)于26天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Figma Context MCP

作者:GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

在你的电脑上运行★ 16,165MIT5个月前更新
安装

Claude Real Video

作者:HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

在你的电脑上运行★ 2,284MIT2个月前更新
安装

Figma MCP Server

作者:figma

The Figma MCP server brings Figma design context directly into your AI workflow.

在云端运行★ 2,15213个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

@rendobar/mcp

Serverless media processing for AI agents.

The official Model Context Protocol server for Rendobar.

Docs · npm · Glama · Discord

@rendobar/mcp is the official Model Context Protocol server for Rendobar, a serverless media processing API. The server runs locally over stdio and reads files straight from your disk, so an AI agent can take a file off your machine, process it on Rendobar's infrastructure, and hand back a hosted URL.

Rendobar covers both sides of media work.

Transform what you have. Run any FFmpeg command against video, audio or images the way you would write it locally. Inspect a file and get a normalized summary plus the full ffprobe report. Compose video from a declarative JSON timeline. Compress to a target size or quality, where the encoder searches candidate encodes and returns the smallest file that clears the bar. Burn in subtitles from SRT, VTT or ASS, or let it transcribe when none is given.

Generate what you do not. Create an image from a text prompt on hosted open-weight diffusion models. Edit up to four reference images from a written instruction, no masks and no coordinates. Upscale on a one-step diffusion restoration model that reconstructs detail rather than only sharpening. The same model-backed layer drives the transcription and keyword highlighting behind animated captions, so this is not an image-only capability.

The job list grows over time, so this README names families rather than types. list_job_types reads the current set live from the registry on every call.

Published to npm as @rendobar/mcp and to the official MCP Registry as com.rendobar/mcp.

Without it

You: Mute the first 3 seconds of intro.mp4.

The agent tells you to install FFmpeg. Then you go looking for how to gate a filter on a timestamp, land on volume=enable='lt(t,3)', and lose another few minutes to quote escaping in your shell. Nobody remembers that syntax, which is the problem.

With it

You: Mute the first 3 seconds of intro.mp4.

upload_file  { "path": "~/clips/intro.mp4" }

// → { "downloadUrl": "https://cdn.rendobar.com/u/abc123/intro.mp4", "sizeBytes": 4821004 }

submit_job { "type": "ffmpeg", "inputs": { "intro.mp4": "https://cdn.rendobar.com/u/abc123/intro.mp4" }, "params": { "command": "-i intro.mp4 -af \"volume=enable='lt(t,3)':volume=0\" -c:v copy out.mp4" } } // → { "jobId": "job_9f2a", "status": "waiting" }

get_job { "jobId": "job_9f2a", "wait": true } // → complete · $0.01 · https://cdn.rendobar.com/o/job_9f2a/out.mp4

The agent writes the filter. Rendobar runs it. Nothing gets installed on your machine, and -c:v copy means the video stream is never re-encoded.

Two more things to ask for

Hit a size budget.

You: Get demo.mov under 25 MB so I can email it.

upload_file  { "path": "~/recordings/demo.mov" }

// → { "downloadUrl": "https://cdn.rendobar.com/u/7c1e/demo.mov", "sizeBytes": 251658240 }

submit_job { "type": "compress.target", "inputs": { "source": "https://cdn.rendobar.com/u/7c1e/demo.mov" }, "params": { "for": "web", "target": { "maxSize": "25MB" } } } // → { "jobId": "job_4b8d", "status": "waiting" }

get_job { "jobId": "job_4b8d", "wait": true } // → complete · https://cdn.rendobar.com/o/job_4b8d/out.mp4 · 23.8 MB

You give it the ceiling, not a bitrate. The encoder searches candidate encodes and returns the smallest file that still clears the quality bar, so you are not guessing at CRF values to land under a mail server's limit.

Generate an image.

You: Make a 1920x1080 title card for a video about deep sea diving.

submit_job   { "type": "image.generate",

"inputs": {}, "params": { "model": "standard", "prompt": "Title card for a deep sea diving documentary. Shafts of light through deep blue water, small diver silhouette, empty space across the upper third for a title.", "width": 1920, "height": 1080 } } // → { "jobId": "job_2fa7", "status": "waiting" }

get_job { "jobId": "job_2fa7", "wait": true } // → complete · https://cdn.rendobar.com/o/job_2fa7/out.png

inputs is empty because nothing is being transformed. Ask for a tier (economy, standard, premium) and the platform picks the model, or pin an exact model id to reach its own controls. Requested dimensions are snapped to what the chosen model can actually render.

The rest of the surface

Six more tools, and the prompts that reach them.

You: What can Rendobar actually do?

list_job_types {}

// → { "jobTypes": [ { "type": "compose", "tag": "Compose", // "summary": "Render a video from a declarative JSON timeline", // "acceptsMedia": ["video", "image", "audio"] }, ... ], // "guidance": "..." }

Read live from the job registry on every call, which is why nothing in this README enumerates job types. A new one appears here without a release.

You: How much credit is left?

get_account {}

// → { "balance": "$4.86", "balanceUsd": 4.86, "plan": "free", "isPro": false, // "limits": { "concurrentJobs": 1, "maxFileSize": "500 MB", "jobTimeoutMin": 60 } }

Worth a call before submitting something expensive.

You: What did I run this morning?

list_jobs { "status": "complete", "limit": 5 }

// → { "jobs": [ { "id": "job_9f2a", "type": "ffmpeg", "status": "complete", // "createdAt": "2026-08-04T09:12:00Z", "cost": "$0.01", // "output": { "url": "https://cdn.rendobar.com/o/job_9f2a/out.mp4" } } ] }

The compact row is enough to find a result you lost. Call get_job when you need the full output.

You: Stop that one, I picked the wrong file.

cancel_job { "jobId": "job_9f2a" }

// → { "id": "job_9f2a", "status": "cancelled" }

Works on waiting, dispatched and running jobs. A running job's upstream execution is stopped too, so you are not billed for work you cancelled.

You: Where can this land once it's done?

list_storage {}

// → { "storage": [ { "id": "prod-media", "provider": "s3", "bucket": "acme-prod-media", // "access": "deliver", "defaultDestination": true, "pending": false } ], // "note": "..." }

The buckets connected on the Storage page, without the endpoint or region an agent has no use for. Use the id in destinations, or as storage:// / in any input.

You: What's already in the archive bucket?

list_storage_files { "storageId": "raw-archive" }

// → { "folders": [ { "prefix": "2026/", "uri": "storage://raw-archive/2026/" } ], // "files": [ { "key": "notes.txt", "size": 800, "lastModified": "2026-09-01T00:00:00.000Z", // "uri": "storage://raw-archive/notes.txt" } ], // "cursor": null }

Every entry carries its own storage:// uri, ready to hand straight to submit_job. Pass a folder's prefix to go one level deeper.

Install

Rendobar has two MCP servers. Pick by whether the agent needs your filesystem.

@rendobar/mcp (this package)Hosted (api.rendobar.com/mcp)
Transportstdio, spawned by your clientStreamable HTTP
Reads local filesYes. That is the reason it existsNo. The server has no disk
AuthAPI keyOAuth in the browser, or a Bearer key
Best forClaude Desktop, Cursor, Cline, Zedclaude.ai, ChatGPT, hosted gateways

Hosted, no API key, one command:

claude mcp add --transport http rendobar https://api.rendobar.com/mcp

Local, for filesystem access. Get a key at app.rendobar.com → Settings → API Keys, then:

claude mcp add rendobar -s user --env RENDOBAR_API_KEY=rb_... -- npx -y @rendobar/mcp

Already ran rb login with the Rendobar CLI? Drop --env. The server finds the credentials file.

Claude Desktop, Cursor, Cline, Windsurf

Same block for all four. Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows). Cursor: ~/.cursor/mcp.json on every OS. Windsurf: ~/.codeium/windsurf/mcp_config.json on every OS. Cline: MCP panel → Configure.

On Linux, use Cursor, Windsurf, Cline, Zed, VS Code or Continue. Claude Desktop has no Linux build, so it is the one client on this list you cannot use there. The server itself runs fine on Linux.

{

"mcpServers": { "rendobar": { "command": "npx", "args": ["-y", "@rendobar/mcp"], "env": { "RENDOBAR_API_KEY": "rb_..." } } } }

Restart the client afterwards.

Zed, VS Code, Continue

Zed uses context_servers instead of mcpServers, in ~/.config/zed/settings.json:

{

"context_servers": { "rendobar": { "source": "custom", "command": "npx", "args": ["-y", "@rendobar/mcp"], "env": { "RENDOBAR_API_KEY": "rb_..." } } } }

VS Code 1.101+, in .vscode/mcp.json, prompts for the key instead of storing it:

{

"servers": { "rendobar": { "command": "npx", "args": ["-y", "@rendobar/mcp"], "env": { "RENDOBAR_API_KEY": "${input:rendobarKey}" } } }, "inputs": [{ "id": "rendobarKey", "type": "promptString", "password": true, "description": "Rendobar API Key" }] }

Continue, in .continue/mcpServers/rendobar.yaml:

type: stdio

command: npx args: ["-y", "@rendobar/mcp"] env: RENDOBAR_API_KEY: rb_...

</details>

Runs on macOS, Linux and Windows. Every release is tested on all three in CI. There are no native dependencies, so architecture does not matter: x64 and arm64 both work. Needs Node 20.10 or later, and the server checks at startup and exits with a clear message on older versions.

Tools

ToolPurpose
upload_fileUpload a local file. Returns a URL to use in submit_job.
list_job_typesEvery active job type, read live. Call this first.
submit_jobSubmit a job of any type.
get_jobStatus and result. Pass wait: true to long-poll for ~50s.
list_jobsRecent jobs.
cancel_jobCancel a waiting, dispatched or running job.
get_accountBalance, plan limits, active job count.
list_storageBuckets connected on the Storage page, for storage:// inputs and destinations.
list_storage_filesFolders and files in a connected bucket, each with its storage:// URI.

Job types

**`ffmp

只显示了开头部分;其余内容请在仓库中阅读

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