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RunAPI MCP Server

核心功能:依托RunAPI生成图片、视频、音乐、音频等媒体,支持任务提交与状态查询。自动识别媒体类型,筛选匹配模型,验证参数后创建任务,必要时向用户确认。典型场景:用户需要生成各类媒体内容或查询任务进度。输入为生成请求或查询指令,输出含任务ID、状态、临时媒体链接(有效期7天)及费用信息,提醒需自行存储以长期使用。

runapi-ai
热度 46.78
最近更新 2026-06-18 16:48:53
分类:创作依赖:MCP 服务应用场景:图像生成 / 视频编辑

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add runapi-mcp
Metadata
name
RunAPI Media Generator
description
Use when the user asks to generate an image, create a video, make music, create audio, synthesize speech, submit a media task, poll a task, or produce generated media through RunAPI. Triggers include "generate an image", "create a video", "make music", "generate audio", "生成图片", "生成视频", "生成音乐", "创建音频", and "check this task".
version
0.1.0

RunAPI Media Generator

Use RunAPI tools to turn a media request into a validated task.

Workflow

  1. Identify the modality and likely action.
  2. Call mcp__runapi__list_models with the narrowest useful filter.
  3. Choose a model from returned data, or ask one clarifying question if required.
  4. Call mcp__runapi__get_model_info with the selected service, action, and model to validate params, constraints, and input rules.
  5. For video, music, or batch requests, ask for confirmation before creating tasks.
  6. Delegate creation to task-executor, or call mcp__runapi__create_task directly when delegation is unavailable.
  7. Present task ID, status, output URLs, and cost fields when available.
  8. Tell the user that RunAPI-generated file URLs are temporary and valid for 7 days, and that durable use requires downloading and storing the generated files in their own storage.

Rules

  • Do not invent model slugs.
  • Do not hardcode prices.
  • Do not retry task creation after timeout.
  • Do not describe generated media as if you inspected it.
  • Use wait=false when the user asks to submit only.
  • Use mcp__runapi__get_task for follow-up status checks.
  • For app/backend integrations, include a storage step for generated images, videos, audio, or other files before treating the workflow as production-ready.