turbo-flow — MCP Server by marcuspat

by marcuspat · MCP Server · ★ 162

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About turbo-flow

Turbo Flow v4.0 — The Ruflo Migration Complete Agentic Development Environment — Ruflo v3.5 + Beads + Worktrees + Agent Teams Built & Presented by Adventure Wave Labs Quick Start • Installation • Plugins • Commands • Migration • Resources About Adventure Wave Labs Adventure Wave Labs is the team behind Turbo Flow a complete agentic development environment built for the Claude ecosystem. We design, build, and maintain the tooling that brings together orchestration, memory, codebase intelligence, and agent isolation into a single streamlined workflow. What's New in v4.0.0 -

agentic-aiagentic-engineeringagentic-frameworkagentic-ragagentic-workflowai-assistantai-toolsanthropic-claudeautonomous-agentsclaude-code

Quick Facts

Stars162
Forks43
LanguageShell
CategoryMCP Server
LicenseMIT
Quality Score53.942/100
Open Issues1
Last Updated2026-06-13
Created2025-08-22
Platformsclaude-code, cli, codex, mcp
Est. Tokens~14k

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Frequently Asked Questions

What is turbo-flow?

turbo-flow is Advanced Agentic Development Environment Supporting Devpods, Rackspace Spot Instances, Github Codespaces, Google Cloud Shell, and more! Features 600+ AI subagents, Claude Flow, SPARC methodology, and. It is categorized as a MCP Server with 162 GitHub stars.

What programming language is turbo-flow written in?

turbo-flow is primarily written in Shell. It covers topics such as agentic-ai, agentic-engineering, agentic-framework.

How do I install or use turbo-flow?

You can find installation instructions and usage details in the turbo-flow GitHub repository at github.com/marcuspat/turbo-flow. The project has 162 stars and 43 forks, indicating an active community.

What license does turbo-flow use?

turbo-flow is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to turbo-flow?

The top alternatives to turbo-flow on Agent Skills Hub include bernstein, AgenticGoKit, claude-historian-mcp. 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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