Pipe2.ai

ai.pipe2Published by pipe2.aiOfficial publisherv1.0.0Updated Oct 24, 2026

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

VerifiedStreamable HTTPWeb executableMedia & DesignAI & ML

Overview

AI-generated overview

Pipe2.ai is a remote MCP server that lets an assistant discover, run and monitor multi-step AI pipelines for video, image, audio and text.

What you can do
List available AI video and image pipelines with name, category, credit cost and required providers, and fetch each pipeline's JSON input schema before running it. Run a pipeline by slug with the given input and receive a run ID for tracking. Check a run's status, output data, error messages, timestamps and generated asset URLs. Request a presigned S3 upload URL for input files such as images, videos or audio, then upload the file contents to that URL.
When to use it
Useful when you want an assistant to generate or process media through hosted AI pipelines, such as producing video, image or audio assets, without wiring up each model provider yourself. Also suited to checking on long-running generation jobs and retrieving their outputs.
Requirements
A remote MCP endpoint at mcp.pipe2.ai over streamable HTTP; no local package, environment variables or headers are declared. Pipelines list a credit cost and required providers, so a Pipe2.ai account with credits is likely needed. Uploading inputs requires network access to the presigned S3 URL.
Before you install
Running pipelines consumes credits, which may mean spending money. The upload flow asks you to send file contents to a presigned S3 URL, so files leave your machine for third-party storage. Generated assets and run outputs are hosted by the service. No authentication is declared in the manifest, so confirm how your account and credits are tied to the connection.

Installation

In SourceWeft

  1. Open Pipe2.ai in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/ai.pipe2%2Fmcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

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

Tools

5

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.

Parametersrun_idrequired

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.

Parameterspipeline_slugrequired

list_pipelines

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

Takes no parameters.

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 (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)

Parametersfilenamerequiredcontent_typerequired

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.

Parametersinputrequiredpipeline_slugrequired

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

83% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts

    Declare a GitHub repository with a README, or serve resource_documentation in the OAuth protected-resource metadata.

  • LicenseNot applicable

    A hosted service is used under its provider's terms, so no license is expected here. This check is left out of the percentage.