# pipe

> pipe — machuraharry-pipe. Use this tool when you need to streamline complex workflows and AI pipelines with a lightweight, dependency-free solution. The pipe tool solves problems related to workflow management, AI integration, and sandboxed agent deployment, providing 198 builtins and a semantic pipeline runtime. It accepts various inputs, including git repositories, and outputs efficient, scalable workflows, making it ideal for use cases requiring seamless server-client interactions and minimal overhead.

Canonical page: https://skillsregistry.net/skills/machuraharry-pipe  
JSON: https://api.skillsregistry.net/v1/skills/machuraharry-pipe

## Description

The first language with built-in MCP (server + client). Semantic Pipeline Runtime: 198 builtins, AI pipelines, sandboxed agents, single ~7 MB binary, zero dependencies.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/MachuraHarry/pipe)

## Use it

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": "machuraharry-pipe"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/machuraharry-pipe` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/machuraharry-pipe/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