mc-agent-toolkit — MCP Server by monte-carlo-data

by monte-carlo-data · MCP Server · ★ 80

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About mc-agent-toolkit

Official Monte Carlo toolkit for AI coding agents. Skills and plugins that bring data and agent observability — monitoring, triaging, troubleshooting, health checks — into Claude Code, Cursor, and more.

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

Quick Facts

Stars80
Forks1
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score42.75/100
Open Issues2
Last Updated2026-05-05
Created2026-02-25
Platformsclaude-code, codex, mcp, python, vscode
Est. Tokens~83k

mc-agent-toolkit alternative? Top 6 similar tools

Looking for a mc-agent-toolkit alternative? If you're comparing mc-agent-toolkit with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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Frequently Asked Questions

What is mc-agent-toolkit?

mc-agent-toolkit is Official Monte Carlo toolkit for AI coding agents. Skills and plugins that bring data and agent observability — monitoring, triaging, troubleshooting, health checks — into Claude Code, Cursor, and mo. It is categorized as a MCP Server with 80 GitHub stars.

What programming language is mc-agent-toolkit written in?

mc-agent-toolkit is primarily written in Python. It covers topics such as agent-observability, agent-skills, ai-agents.

How do I install or use mc-agent-toolkit?

You can find installation instructions and usage details in the mc-agent-toolkit GitHub repository at github.com/monte-carlo-data/mc-agent-toolkit. The project has 80 stars and 1 forks, indicating an active community.

What license does mc-agent-toolkit use?

mc-agent-toolkit is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to mc-agent-toolkit?

The top alternatives to mc-agent-toolkit on Agent Skills Hub include ok-skills, affiliate-skills, agnix. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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