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Pipe2.ai

ai.pipe2/mcp · v1.0.0

Has write/delete tools

Measured by MCP Station

Last check	Reachable
Checked at	—
Check success 7 / 30 days	—
First-try success 30 days	—
Median response	—
Lookups 30 days	—
Authentication	No auth
MCP version	2025-06-18
Rank score	—
Declared risk	Has destructive tools (destructiveHint)
Capabilities declared	prompts, resources, tools
Tool definitions	5 tools · with description 100% · input schema is an object 100% · read/destructive hints 100%

Run multi-step AI pipelines for video, image, audio and text: upload media, run, poll results.

streamable-http · https://mcp.pipe2.ai/mcp

claude mcp add --transport http mcp https://mcp.pipe2.ai/mcp

{
  "mcpServers": {
    "mcp": {
      "url": "https://mcp.pipe2.ai/mcp"
    }
  }
}

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 to the upload_url (pr
run_pipeline write/delete
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.

Website · JSON · Text for agents · Registry updated 2026-07-31