mc-agent-toolkit: Official Monte Carlo toolkit for AI coding agents

by monte-carlo-data · MCP Server · ★ 93

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install mc-agent-toolkit

/plugin marketplace add monte-carlo-data/mc-agent-toolkit
/plugin install mc-agent-toolkit@mc-marketplace

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 74/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-observabilityagent-skillsai-agentsclaude-codecodex-skillscursordata-observabilitydata-qualitymcpmonte-carlo

Quick Facts

Stars93
Forks5
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score74/100
Open Issues8
Last Updated2026-10-22
Created2026-02-25
Platformsclaude-code, codex, mcp, python, vscode
Est. Tokens~15k

About mc-agent-toolkit

MC Agent Toolkit Monte Carlo's official toolkit for AI coding agents. Brings data observability — lineage, monitoring, validation, alerting, and metadata ingestion — directly into your development workflow. The toolkit bundles multiple skills into a single plugin that works across supported editors.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse MCP Server tools