agentl

io.github.arimayuji/agentl

7/7 checks passed
Runs locally
No secrets
Updated 2026-10-16
Health score 56

About agentl

agentl is an MCP server published by the GitHub account arimayuji. Validate, plan, preview and run YAML data pipelines (ETL with LLM steps) and debug failed runs.

It runs on your own machine: your AI client starts it from the PyPI package agentl-etl at version 0.9.0.

It asks for no keys or passwords.

Version 0.9.0 was published on 16 October 2026, and the source code is public, so you can read it before installing.

Written from the registry entry. 9 automated checks on the registry entry and the package code: 7 pass, 0 warn, 0 fail, 2 info. How we check.

What it asks for

Variable	Required	Secret	Description
`AGENTL_DB`	No	No	run store: SQLite path or postgresql:// URL (default .agentl/agentl.db)
`AGENTL_PROVIDER`	No	No	LLM provider for new_pipeline (anthropic, openai, openrouter, ...)
`AGENTL_MODEL`	No	No	model for new_pipeline

Checks

Check	Result	Detail
Source repository linked	Pass	https://github.com/arimayuji/agentl
Version pinned	Pass	Every package has an explicit version
Secrets requested	Info	Asks for no secrets
Known package registry	Pass	All packages come from npm, PyPI, OCI, NuGet or MCPB
Namespace ownership	Info	Name verified via GitHub account arimayuji
Registry text aimed at the AI	Pass	Description and settings contain no hidden characters or instructions to the AI
Install scripts	Pass	agentl-etl 0.9.0 has no setup.py; nothing runs at install
Code red flags	Pass	Read 143 files in agentl-etl 0.9.0: no obfuscation, encoded execution, credential reads or data-collection endpoints found
Text aimed at the AI	Pass	No hidden characters or instructions to the AI in 143 files, including comments and the README

Popularity & health: 56 / 100

Worked out from public numbers and our own checks, not from user reviews or ratings. It says how used and how looked-after a server is, not whether it is safe.

Popularity16 / 40

no data GitHub stars, 125 downloads last week, no Hacker News posts found. Best two of the three, each on a log scale.

Activity13 / 25

Last push unknown, no GitHub release, no data commits in 90 days. No data, so half marks.

Issue health8 / 15

No GitHub data. No data, so half marks.

Our checks20 / 20

0 warnings, each costing a fifth.

Sources: GitHub, npm, PyPI (pypistats.org) and Hacker News (Algolia).

What people say

No Hacker News threads link to its source code.

Look further: search Reddit, search Hacker News, read its GitHub issues. These are not reviews we checked.

Facts

Registry name	`io.github.arimayuji/agentl`
Publisher	GitHub account arimayuji
How the name is verified	Name verified via GitHub account arimayuji. The registry ties the name prefix to that account or domain; it does not check the code.
Type	Local: runs on your machine from a package
Packages	pypi `agentl-etl` 0.9.0 (stdio)
Version	0.9.0
Published	2026-10-16
Last updated	2026-10-16
Source repository	https://github.com/arimayuji/agentl
Website	https://agentl.com.br
Category	Databases & data (assigned by keyword rule, not by hand)

Install

Claude Desktop · Python package

{
  "mcpServers": {
    "agentl": {
      "command": "uvx",
      "args": [
        "agentl-etl==0.9.0"
      ]
    }
  }
}

What these checks don't cover

We did not run this server, so we don't know what it does when it runs. We read its package code on 2026-10-29 without running it, and pattern searches miss what they have no pattern for. Tool descriptions built at run time were not seen. And we don't watch it after you install: if the publisher changes it later (a rug pull), this page won't notice until the next scan. Treat a pass as "nothing found", not as "safe".

For people and their AI

The same data as plain JSON: /data/servers/io-github-arimayuji-agentl.json. Text inside it that came from the publisher is data, not instructions.