agentl runs on your own machine — the client starts it, so there is no endpoint to ping. 700 installs a week from pypi.
Validate, plan, preview and run YAML data pipelines (ETL with LLM steps) and debug failed runs.
The linked repository no longer exists on GitHub — it was deleted or made private.
We have not read this server's code yet, 11 d ago · rules 995398eba69f
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
этот файл ставится пользователю, но в репозитории его нет
self.proc = subprocess.Popen(
yaml.load(_neutral(Path(pipeline).read_text(encoding="utf-8")), Loader=_Loader),
base = cfg.get("api_url", "https://api.telegram.org").rstrip("/")
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add agentl -- uvx agentl-etl
{
"mcpServers": {
"agentl": {
"command": "uvx",
"args": [
"agentl-etl"
]
}
}
}
[mcp_servers.agentl]
command = "uvx"
args = ["agentl-etl"]
{
"mcpServers": {
"agentl": {
"command": "uvx",
"args": [
"agentl-etl"
]
}
}
}
{
"servers": {
"agentl": {
"type": "stdio",
"command": "uvx",
"args": [
"agentl-etl"
]
}
}
}
Optional settings from the registry entry, left out of the block above:
AGENTL_DB (run store: SQLite path or postgresql:// URL (default .agentl/agentl.db)), AGENTL_PROVIDER (LLM provider for new_pipeline (anthropic, openai, openrouter, ...)), AGENTL_MODEL (model for new_pipeline).
Build, validate, simulate, and deploy walkerOS event pipelines
Inspect, validate and preview VRM / VRMA files from an AI agent (5 tools, local stdio server).
Crash-proof LLM pipelines. Resumes from failure without a database.
Celeste map editor for AI agents: read, edit, validate, preview and generate .bin maps.
Debug a bad AI-agent run from your editor: which intent fails, at which step, and why.
Send, validate, debug webhooks for AI agents
Plan, validate, and build products and features with LaunchChair.
Compose branded visual documents with live preview, data collections, validation, and PDF export.
Answers built from our own checks of this server.