Pipe2.ai

Last 30 days

Uptime

100%

Response time

131 ms typical, 131 ms slowest 5%

Last check

4 h ago

Next check

in 2 h

How to call it

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "pipe2-ai": {
      "type": "http",
      "url": "https://mcp.pipe2.ai/mcp"
    }
  }
}

5 tools

• get_pipeline_run_status

  Check the status of a pipeline run. Returns status (pending/running/completed/failed), output data, error messages, timestamps, and generated asset URLs.

• get_pipeline_schema

  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.

• list_pipelines

  List all available AI video/image pipelines. Returns name, slug, description, category, credit cost, and required providers for each active pipeline.

• request_upload

  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

• run_pipeline

  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.

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