Pipe2.ai
Run multi-step AI pipelines for video, image, audio and text: upload media, run, poll results.
Sollte ich dies verwenden
Qualität und Sicherheit
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.
Installieren
Installation mit einem Klick
Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:
{
"mcpServers": {
"mcp": {
"url": "https://mcp.pipe2.ai/mcp"
}
}
}Remote-Endpunkte
https://mcp.pipe2.ai/mcpstreamable-httpWas es kann
Tool-Inventar
Tools (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.
Eingabe-Schema
{
"type": "object",
"properties": {
"run_id": {
"description": "The pipeline run ID returned by run_pipeline",
"type": "string"
}
},
"required": [
"run_id"
]
}Ausgabe-Schema
{
"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.
Eingabe-Schema
{
"type": "object",
"properties": {
"pipeline_slug": {
"description": "The slug identifier of the pipeline (e.g., 'image-generator', 'video-generator')",
"type": "string"
}
},
"required": [
"pipeline_slug"
]
}Ausgabe-Schema
{
"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.
Eingabe-Schema
{
"type": "object",
"properties": {},
"required": []
}Ausgabe-Schema
{
"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)
Eingabe-Schema
{
"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"
]
}Ausgabe-Schema
{
"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.
Eingabe-Schema
{
"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"
]
}Ausgabe-Schema
{
"type": "object",
"properties": {
"run_id": {
"type": "string"
},
"workflow_id": {
"type": "string"
}
},
"required": [
"run_id",
"workflow_id"
]
}Community
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