Is Monte Carlo Agent Toolkit safe and trustworthy?

tashan scores Monte Carlo Agent Toolkit on public evidence — tashan score 60.0/100, it is currently active. Audit scope: OSV advisories, install-time scripts, build provenance and declared permission surface. We do not review source code or execute the capability.

How do I install Monte Carlo Agent Toolkit?

Configure it from its source repository — it is a remote / registry server.

Who maintains Monte Carlo Agent Toolkit?

16 GitHub contributors, source: monte-carlo-data/mc-agent-toolkit.

‹ The Index

Monte Carlo Agent Toolkit

plugin

Monte Carlo Agent Toolkit gives AI coding agents data observability superpowers across the full data lifecycle. Before querying a table, the agent checks freshness, alerts, and monitor coverage. When an alert fires, it triages, traces root cause, and proposes fixes. When code changes a dbt model, it surfaces blast radius before the edit lands. It plans monitor coverage on new domains, tunes noisy monitors, diagnoses slow pipelines, identifies storage waste, and generates validation queries for P

Works with: Claude Code (native)
native: this artifact type is that client's own format

Work: Data quality · Observability · Incident response

Who it is for: Data engineer · DevOps / SRE

Install (Claude Code):

/plugin marketplace add anthropics/claude-plugins-community
/plugin install monte-carlo-agent-toolkit@claude-community

Not graded: its only documentation never names it. A grade read off another project’s document would borrow its credit, or its blame.

tashan score: 60.0
Adoption: 1 repos
Upkeep: 93.0
Freshness: 84.0
Evidence coverage: 84% of the inputs this score can use — the rest are unknown, and the score is discounted for it
Health: active
GitHub stars: 90
Contributors: 16
License: Apache-2.0

Security audit

Not scanned yet. We audit npm-published capabilities for known advisories, install-time scripts and permission surface; this one has no npm package we can resolve, or has not reached the queue.

You searched for one. Check the rest of your stack:

npx tashan-cli doctor

Reads the config already on your machine and names what is dead, deprecated or running code at install time. No account, nothing uploaded.

tashan Pro$6/mo

Monte Carlo Agent Toolkit scores 60 today. Pro keeps the series, so you can see whether that is a project getting better or one on its way down.

The whole series behind any row, back to the first day we measured it
The replacement, named — not just the news that something died
tashan doctor over your own config, on your own machine

Start a 7-day trial › Everything measured on this page stays free.

Show your score

Measured this well? Put the live badge in your README — it updates as the score does.

[![tashan](https://tashan.sh/badge/plugin-monte-carlo-data-mc-agent-toolkit-monte-carlo-agent-toolkit.svg)](https://tashan.sh/capability/plugin-monte-carlo-data-mc-agent-toolkit-monte-carlo-agent-toolkit.html)

source ↗ · plugin:monte-carlo-data/mc-agent-toolkit/monte-carlo-agent-toolkit

Everything on this page is public evidence and free. What it cannot know is whether you run this — check your whole config, free, in the browser. tashan Pro adds the series behind each row and names a replacement for anything dying.

Already running this? Check your whole config — free, in your browser, nothing installed. Or npx tashan-cli doctor locally, which sends nothing at all.

Measured 2026-09-13 · scorer s5 · how · something wrong here?