# fast-pyairbyte

> Use this tool when you need to streamline data integration and create custom pipelines efficiently. It solves problems of manual pipeline configuration and supports various Airbyte connectors, allowing for seamless data flow. With a single prompt, it takes in connector specifications and outputs a fully functional data pipeline in code.

Canonical page: https://skillsregistry.net/skills/quintonwall-fast-pyairbyte  
JSON: https://api.skillsregistry.net/v1/skills/quintonwall-fast-pyairbyte

## Description

fast-pyairbyte lets you create a data pipeline in code ,from any Airbyte connector,  with a single prompt.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **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:** [Glama](https://glama.ai/mcp/servers/iy9pi7665w)
- **Repository:** <https://github.com/quintonwall/fast-pyairbyte>

## 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": "quintonwall-fast-pyairbyte"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/quintonwall-fast-pyairbyte` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/quintonwall-fast-pyairbyte/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