Pipe2.ai MCP Server

by pipe2 Your server? Claim it

answering

Pipe2.ai is answering right now. Last checked 1 min ago. It exposes 5 tools.

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

Uptime history 48 days of history

48 days agonow

100.0%

Uptime 24h

92 of 92 checks

Tools

read from the server

215 ms

Response time

average over 24h

open, no key

Access

streamable-http

Nothing serious here today

Today is the operative word: we check Pipe2.ai every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 1 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

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

~/Library/Application Support/Claude/claude_desktop_config.json

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

~/.codex/config.toml

[mcp_servers.mcp]
url = "https://mcp.pipe2.ai/mcp"

.cursor/mcp.json

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

.vscode/mcp.json

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

Available tools 5

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

pipeline

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.

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.

pipelines

list_pipelines

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

request

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)

Endpoints

URL	Transport	State	Latency	Checked
https://mcp.pipe2.ai/mcp	streamable-http	answering	131 ms	1 min ago

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Pipe2.ai — questions

Answers built from our own checks of this server.

What can Pipe2.ai do?

It exposes 5 tools, read directly from the server on our last check. Among them: get_pipeline_run_status, get_pipeline_schema, list_pipelines, request_upload, run_pipeline. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

Is Pipe2.ai working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 92 of 92 checks got a reply (100.0%), average response time 215 ms. The bar chart above shows every period we have measured.

How do I connect Pipe2.ai?

Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does Pipe2.ai need an API key?

No. Pipe2.ai completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 5 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is Pipe2.ai?

It answers our handshake in 215 ms on average, which is faster than 64% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.