runninghub-image
Summary: runninghub-image is a WorkBuddy/MCP connector shell over the runninghub-mcp engine (--scope image) that lets an AI client find, run, and fetch results from RunningHub's 90+ image models (text-to-image, image-to-image, editing, upscaling) — and, via the same tool set, any other model category.
Search models (
runninghub_search_models): find models by keyword (seedream, 可灵, 数字人, tts, suno), group (text-to-image, image-to-video…), or category (image/video/audio/other/all), returning the endpoint to call.Browse models (
runninghub_list_models): list models by required category, with optional group filter and limit.Submit tasks (
runninghub_submit_task): post params (e.g. a prompt) to a model endpoint, optionally waiting automatically until completion; returns a taskId. Requires an enterprise shared API Key.Query a task (
runninghub_query_task): single status/result check via the v2 standard-model API or the legacy workflow/AI-app API.Wait for a task (
runninghub_wait_task): poll every 5s until SUCCESS/FAILED or timeout, returning result file URLs.Upload files (
runninghub_upload_file): send a local image/video/audio/zip and get a fileName for workflow node inputs.Download results (
runninghub_download_file): save result URLs to a local path, completing the generate-to-disk loop.
Provides access to TED talks transcripts metadata assembly stderr generated unusual provenance.
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., "@runninghub-image Generate a cyberpunk city night scene with seedream"
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.
RunningHub 图像连接器 · RunningHub Image Connector
开发者:AI芳程式 | 问题反馈或建议:zzdh518 Developer: AI芳程式 (AI Fangchengshi) | Feedback & suggestions: zzdh518
文生图 · 图生图 · 图像编辑 · 放大修复,90+ 图像模型 API
Text-to-image · image-to-image · editing · upscaling — 90+ image model APIs
🎨 品类 / Category:图像 · 90+ 图像模型 | 形态 / Form:WorkBuddy 连接器包(MCP + Skill)+ 自带 server/ 源码,可完全独立部署
面向 WorkBuddy 连接器市场的成品提交包(MCP + Skill 方案),同时适用于任意支持 MCP 的客户端。底层 MCP 服务器来自 runninghub-mcp,通过 --scope image 限定能力范围。
A ready-to-submit WorkBuddy connector package (MCP + Skill). The underlying MCP server is runninghub-mcp, restricted to --scope image.
30 秒判断要不要用:主图详情页要量产、模特图要换背景、老图要放大;排队久、中文提示词水土不服、出图不可控 —— 这个仓库就是为它准备的。 30-second check (EN): Product hero shots, background swaps and 4K upscaling — Chinese prompts work as-is. 下面是它的完整定位、能解决的问题,以及家族里另外 5 个仓库。Below: what this repo is, what it solves, and the other five repos in the family.
🧭 本仓库在家族里的位置 / Where this repo fits
本仓库 / This repo | 🎨 runninghub-image-connector — 图像连接器 |
品类 / Category | 图像 · 90+ 图像模型 |
形态 / Form | WorkBuddy 连接器壳(MCP + Skill,引擎经 npm 分发) |
独立可用 / Standalone | ✅ 单独安装即可用,一条 |
联动可用 / Interop | ✅ 与家族其它 5 个仓库共用同一套 RunningHub 账号与 API Key,可任选组合安装 |
适合谁 / Who it's for | 电商设计 / 社媒运营 / 插画师 / 品牌视觉 |
解决的痛点 / Pain it kills | 主图详情页要量产、模特图要换背景、老图要放大;排队久、中文提示词水土不服、出图不可控。 |
给你的价值 / What you get | 90+ 图像模型(Seedream / 千问 / 悠船 / Topaz)随选随切,文生图、图生图、精修、4K 放大全在一个对话里,中文提示词原样可用。 |
🚀 两种用法 / Two ways to use it
A. 只装这一个(独立部署,最小依赖) — 你只想在这一个品类上用 AI:
WorkBuddy 用户:在连接器市场搜「RunningHub」,装这一个就行(见下方「安装」)。
任意 MCP 客户端 / 开发者:一条
npx命令,核心引擎经 npm 分发(本仓库是连接器壳,不含引擎源码):
# 方式一:npx 直接跑(推荐,需要 runninghub-mcp 已发布到 npm)
npx -y runninghub-mcp@latest --scope image
# 方式二:写进 MCP 客户端配置
# { "command": "npx", "args": ["-y", "runninghub-mcp@latest", "--scope", "image"] }
--scope让后端只加载本品类模型:启动更快、上下文更省、也更不容易挑错模型。
B. 家族联动(图 + 视频 + 音频一次到位) — 你想让 AI 一次干完整条链路:
同一个 API Key 下装多个连接器,或在 WorkBuddy 里直接装全能连接器 runninghub-connector——一个顶四个;开发者还可以直接用核心引擎 runninghub-mcp 自己拼。
🔗 家族全部仓库 / The whole family
仓库 / Repo | 品类 / Category | 一句话 / In one line | |
🏠 | 家族总入口 · 导航与安装指南 | 6 个包的介绍、安装指南与 4 个可直接上传 WorkBuddy 的连接器 zip,一次看全 | |
⚙️ | 核心引擎 · MCP 服务器(npm 包,非连接器) | 给任何 MCP 客户端装上 RunningHub 的 350+ 模型双手 | |
🧰 | 全能 · 图 + 视 + 音 + 3D + 工作流 + LLM | 一个连接器顶掉一堆账号:350+ 模型,一句话从出图切到出片再切到配音 | |
🎬 | 视频 · 200+ 视频模型 | 一条片子不用换五个平台,首尾帧与数字人口播全覆盖 | |
🔊 | 音频 · 50+ 音频模型 | 配音、配乐、人声分离一站搞定,不用买音色包 |
💡 不确定装哪个? 先装全能连接器 runninghub-connector 一个就够; 只做图片就装 runninghub-image-connector, 只做视频装 runninghub-video-connector, 只做配音/音乐装 runninghub-audio-connector, 要自己二次开发从 runninghub-mcp 入手。
全部由 AI芳程式 开发,问题反馈或建议请联系 zzdh518。
Related MCP server: laozhang-image MCP
🐣 保姆级小白指南 / Beginner's guides
中文:GUIDE.md — 完全没用过 AI 产品也能照着用起来
English: GUIDE_EN.md — step-by-step for absolute beginners
前置条件 / Prerequisites
API Key — 在 RunningHub API 管理页面 点「新建」创建
账户余额 — 用邀请码注册即送 500 RH 币(可免费生成不少图片和视频);用完后到 RunningHub 官网 充值
还没有账号?RunningHub 邀请注册链接 —— 填写邀请码
zlhtnu0f,可得 500 RH 币,可以免费生成不少图片和视频哦!
安装 / Install
WorkBuddy 连接器市场:搜索「图像连接器」安装,连接时粘贴 API Key。
手动配置 / Manual MCP config:
{
"mcpServers": {
"runninghub-image": {
"type": "stdio",
"command": "npx",
"args": ["-y", "runninghub-mcp@latest", "--scope", "image"],
"env": { "RUNNINGHUB_API_KEY": "你的 API Key / your API key" }
}
}
}一键安装 / One-click install:把 INSTALL_PROMPT.md 里的提示词复制给你的 AI Agent,它会自动安装并引导配置。Copy the prompt from INSTALL_PROMPT.md into your agent.
能做什么 / What you can ask
「用 seedream 文生图画一张赛博朋克城市夜景」
「把这张照片放大到 4K」
「用千问图像编辑,把图片背景换成海边」
"Generate a cyberpunk city night scene with seedream"
"Upscale this photo to 4K"
"Change the background to a beach with Qwen image edit"
工具 / Tools
7 个工具(模型检索 / 提交 / 等待 / 上传下载),详见 skills/image-usage/SKILL.md 与 runninghub-mcp 工具表。
仓库结构 / Repo layout
├── connector-meta.json # WorkBuddy 连接器元信息(中英名称/描述/示例)
├── mcp.json # MCP 服务器连接配置(指向 npm 上的 runninghub-mcp)
├── token-schema.json # 用户自填 Token 表单(API Key)
├── icon.svg # 市场图标(芳字主视觉 + AI芳程式 署名)
├── GUIDE.md / GUIDE_EN.md # 保姆级小白指南(中/英)
├── skills/ # AI 使用说明(SKILL.md)
├── tools/pack.mjs # 打包成可上传的 zip
└── .github/workflows/ # 打 tag 自动打包发布🔒 本仓库是连接器壳:只包含安装、配置、指南与使用说明,不包含 MCP 服务器源码。 引擎(npm 包
runninghub-mcp)由作者另行分发,源码闭源。🔒 This repo is a connector shell: install/config/guides only. The MCP server engine (npm package
runninghub-mcp) is distributed separately by the author and is closed-source.
打包提交 / Package & submit
node tools/pack.mjs # 生成 dist/runninghub-image-<version>.zip把 zip 上传到 WorkBuddy 开发者后台审核即可。Upload the zip to the WorkBuddy developer backend.
许可证 / License
MIT © AI芳程式
Available Tools
7 toolsrunninghub_download_fileC
把任务结果文件(URL)下载到本地指定路径。
Inputs: url (required), savePath (required).
runninghub_list_modelsC
按类别浏览 RunningHub 模型目录。category=image|video|audio|other。
Inputs: category (required), group, limit.
runninghub_query_taskA
查询 RunningHub 任务状态与结果(单次查询)。v2 用于标准模型任务;legacy 用于工作流/AI 应用任务。
Inputs: taskId (required), apiVersion.
runninghub_search_modelsB
搜索 RunningHub 模型目录(350+ 标准模型 API 端点)。按关键词/类别/分组查找模型,返回可用的 endpoint 与说明。类别:image=图像、video=视频、audio=音频、other=其他(3D 等)。找到模型后用 runninghub_submit_task 提交任务。
Inputs: group, limit, keyword, category.
runninghub_submit_taskA
提交 RunningHub 标准模型任务。先用 runninghub_search_models 找到目标模型的 endpoint,再把该模型文档要求的参数放进 params。返回 taskId,可用 runninghub_wait_task 等待结果。注意:标准模型 API 需要企业级-共享 API Key。
Inputs: endpoint (required), wait, params, waitTimeoutSec.
runninghub_upload_fileA
上传本地文件(图片/视频/音频/压缩包)到 RunningHub,返回 fileName。工作流/AI 应用的图片、音频、视频节点参数请把该 fileName 填入 fieldValue。
Inputs: filePath (required).
runninghub_wait_taskA
轮询等待 RunningHub 任务完成(每 5 秒查询一次,直到 SUCCESS / FAILED 或超时)。返回结果文件 URL 列表。
Inputs: taskId (required), apiVersion, timeoutSec, intervalSec.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 7 tools
Most tools have clearly distinct purposes: submit/query/wait tasks, upload/download files. However, search_models and list_models both retrieve the model catalog, and an agent may need to read descriptions carefully to choose between keyword search and category browsing. The overlap is minor but present.
All tool names follow the same predictable pattern: runninghub_ prefix plus verb_noun (search_models, list_models, submit_task, query_task, wait_task, upload_file, download_file). The snake_case convention is consistent throughout with no deviations.
Seven tools is a well-scoped set for an image generation service. Each tool covers a necessary step in the workflow: discovery, submission, monitoring, and file transfer. No tool feels redundant or excessive.
The surface covers the core lifecycle: finding models, submitting tasks, polling for results, and uploading/downloading files. Minor gaps exist, such as no explicit task cancellation and no tool to submit workflow/AI-app tasks despite query_task mentioning legacy support for them.
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