Pipe2.ai
Run multi-step AI pipelines for video, image, audio and text: upload media, run, poll results.
사용해야 할까요
품질 및 안전성
도구 정의와 프로토콜 준수에 대한 자동 분석을 기반으로 합니다.
컨텍스트 비용
이는 서버의 도구가 모델의 컨텍스트에 로드될 때마다 소비되는 대략적인 토큰 수입니다. 수치가 높을수록 다른 작업에 사용할 수 있는 주의가 줄어듭니다.
설치
원클릭 설치
`claude_desktop_config.json` 파일에 다음을 추가하세요:
{
"mcpServers": {
"mcp": {
"url": "https://mcp.pipe2.ai/mcp"
}
}
}원격 엔드포인트
https://mcp.pipe2.ai/mcpstreamable-http할 수 있는 일
도구 목록
도구 (5)
🟢get_pipeline_run_status(run_id)
Check the status of a pipeline run. Returns status (pending/running/completed/failed), output data, error messages, timestamps, and generated asset URLs.
입력 스키마
{
"type": "object",
"properties": {
"run_id": {
"description": "The pipeline run ID returned by run_pipeline",
"type": "string"
}
},
"required": [
"run_id"
]
}출력 스키마
{
"type": "object",
"properties": {
"agent_actual_credits_mc": {
"type": "integer"
},
"assets": {
"items": {
"properties": {
"created_at": {
"type": "string"
},
"id": {
"type": "string"
},
"thumbnail_url": {
"type": "string"
},
"type": {
"type": "string"
},
"url": {
"type": "string"
}
},
"required": [
"id",
"type",
"url",
"thumbnail_url",
"created_at"
],
"type": "object"
},
"type": "array"
},
"completed_at": {
"type": "string"
},
"created_at": {
"type": "string"
},
"credits_charged": {
"type": "integer"
},
"error_message": {
"type": "string"
},
"id": {
"type": "string"
},
"input": {},
"output": {},
"parent_run_id": {
"type": "string"
},
"pipeline": {
"properties": {
"cancellable": {
"type": "boolean"
},
"input_schema": {},
"name": {
"type": "string"
},
"output_schema": {},
"slug": {
"type": "string"
},
"translations": {
"items": {
"properties": {
"locale": {
"type": "string"
},
"name": {
"type": "string"
}
},
"required": [
"locale",
"name"
],
"type": "object"
},
"type": "array"
},
"ui_schema": {}
},
"required": [
"name",
"slug",
"output_schema",
"input_schema",
"ui_schema",
"cancellable",
"translations"
],
"type": "object"
},
"share_token": {
"type": "string"
},
"share_watermark": {
"type": "boolean"
},
"status": {
"type": "string"
},
"workflow_execution": {
"properties": {
"close_time": {
"type": "string"
},
"start_time": {
"type": "string"
},
"status": {
"type": "integer"
}
},
"required": [
"status",
"start_time",
"close_time"
],
"type": "object"
}
},
"required": [
"id",
"status",
"input",
"output",
"error_message",
"credits_charged",
"parent_run_id",
"agent_actual_credits_mc",
"created_at",
"completed_at",
"share_token",
"share_watermark",
"pipeline",
"assets",
"workflow_execution"
]
}🟢get_pipeline_schema(pipeline_slug)
Get the input schema for a specific pipeline. Returns the JSON Schema describing required and optional input fields. Use this before running a pipeline to understand what inputs are needed.
입력 스키마
{
"type": "object",
"properties": {
"pipeline_slug": {
"description": "The slug identifier of the pipeline (e.g., 'image-generator', 'video-generator')",
"type": "string"
}
},
"required": [
"pipeline_slug"
]
}출력 스키마
{
"type": "object",
"properties": {
"category": {
"type": "string"
},
"input_schema": {
"type": "object"
},
"name": {
"type": "string"
},
"providers": {
"items": {
"type": "string"
},
"type": "array"
},
"slug": {
"type": "string"
}
},
"required": [
"slug",
"name",
"category",
"input_schema"
]
}🟢list_pipelines
List all available AI video/image pipelines. Returns name, slug, description, category, credit cost, and required providers for each active pipeline.
입력 스키마
{
"type": "object",
"properties": {},
"required": []
}출력 스키마
{
"type": "object",
"properties": {
"pipelines": {
"items": {
"properties": {
"category": {
"type": "string"
},
"description": {
"type": "string"
},
"models": {
"items": {
"type": "string"
},
"type": "array"
},
"name": {
"type": "string"
},
"providers": {
"items": {
"type": "string"
},
"type": "array"
},
"slug": {
"type": "string"
}
},
"required": [
"slug",
"name",
"description",
"category",
"providers",
"models"
],
"type": "object"
},
"type": "array"
}
},
"required": [
"pipelines"
]
}🟡request_upload(content_type, filename)
Request a presigned S3 upload URL for a file. Use this for pipeline inputs that require file URLs (e.g., images, videos, audio). **Two-step upload flow:** 1. Call this tool with filename and content_type to get a presigned upload URL and final asset URL 2. PUT the file contents to the upload_url (presigned, expires in 5 minutes) 3. Use the asset_url as the input value when running a pipeline Supported content types: image/* (max 10MB), video/* (max 50MB), audio/* (max 20MB)
입력 스키마
{
"type": "object",
"properties": {
"content_type": {
"description": "MIME type of the file (e.g., 'image/jpeg', 'image/png', 'video/mp4', 'audio/mpeg')",
"type": "string"
},
"filename": {
"description": "Name of the file to upload (e.g., 'photo.jpg', 'video.mp4')",
"type": "string"
}
},
"required": [
"filename",
"content_type"
]
}출력 스키마
{
"type": "object",
"properties": {
"asset_url": {
"type": "string"
},
"key": {
"type": "string"
},
"upload_url": {
"type": "string"
}
},
"required": [
"upload_url",
"asset_url",
"key"
]
}🔴run_pipeline(input, pipeline_slug)
Run an AI pipeline by slug with the given input. Use list_pipelines to discover available pipelines and get_pipeline_schema to see required inputs. Returns a run ID for tracking status.
입력 스키마
{
"type": "object",
"properties": {
"input": {
"description": "Pipeline input fields as a JSON object. Use get_pipeline_schema to see required fields for each pipeline.",
"properties": {},
"type": "object"
},
"pipeline_slug": {
"description": "The slug identifier of the pipeline to run (e.g., 'image-generator', 'video-generator')",
"type": "string"
}
},
"required": [
"pipeline_slug",
"input"
]
}출력 스키마
{
"type": "object",
"properties": {
"run_id": {
"type": "string"
},
"workflow_id": {
"type": "string"
}
},
"required": [
"run_id",
"workflow_id"
]
}커뮤니티
증거