# Pipe2.ai

> Pipe2.ai — ai-pipe2-mcp. Use this tool when you need to process multimedia data through complex AI workflows, solving problems such as automated content analysis, data enrichment, and machine learning model deployment. Pipe2.ai takes in various media types, including video, image, audio, and text, and outputs processed results after running multi-step pipelines. Ideal for use cases requiring sequential AI tasks, such as object detection, sentiment analysis, and speech recognition.

Canonical page: https://skillsregistry.net/skills/ai-pipe2-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ai-pipe2-mcp

## Description

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

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-02

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.pipe2%2Fmcp)

## Use it

MCP endpoint published by the skill: `https://mcp.pipe2.ai/mcp`

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "ai-pipe2-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-pipe2-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-pipe2-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt