maestro-flow — security grade SAFE, quality 68/100

Security audit verdict: SAFE · quality 68/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by catlog22 · MCP Server · ★ 556

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

🔒 Is maestro-flow safe to install? View the security audit →

About maestro-flow

Maestro-Flow Intent-Driven Workflow Orchestration for the Multi-Agent Era Describe what you want. Maestro figures out how to get there. English  |  简体中文 Most AI coding tools let you run one agent on one task. Maestro-Flow orchestrates multiple agents across an entire development lifecycle — from brainstorming to deployment — with an adaptive decision engine, a self-reinforcing knowledge graph, and a real-time visual dashboard. Two Pillars Maestro-Flow is built on two interconnected systems that reinforce each other: ┌─────────────────────────────────────┐ │ Maestro-Flow │ │ │ ┌──────────────┴──────────────┐ ┌──────────────────┴───────────────┐

ai-agentsclaude-codeclicodexgeminiknowledge-graphmcpmulti-agenttypescriptworkflow-orchestration

Quick Facts

Stars556
Forks68
LanguageTypeScript
CategoryMCP Server
Quality Score68.3143240918206/100
Open Issues1
Last Updated2026-09-21
Created2026-03-17
Platformsclaude-code, cli, codex, gemini, mcp, node
Est. Tokens~17k

Compatible Skills

These tools work well together with maestro-flow for enhanced workflows:

  • Multi-AI-Workflow — semantic(0.31)+complementary+same_lang+similar_pop+shared_platform (61%)
  • pi-dynamic-workflows — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)
  • octogent — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)
  • optio — semantic(0.26)+complementary+same_lang+similar_pop+shared_platform (59%)
  • openrig — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)

maestro-flow alternative? Top 6 similar tools

Looking for a maestro-flow alternative? If you're comparing maestro-flow 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.

  • Overture by SixHq · ⭐ 641

    Overture is an open-source, locally running web interface delivered as an MCP (Model Context Protocol) server

  • octocode by Muvon · ⭐ 475

    Structural code intelligence for AI agents — semantic search, knowledge graphs, and a built-in MCP server in o

  • sudocode by sudocode-ai · ⭐ 292

    Lightweight agent orchestration dev tool that lives in your repo

  • claude-code-open by kill136 · ⭐ 158

    Open source AI coding platform with Web IDE, multi-agent system, 37+ tools, MCP protocol. MIT licensed.

  • gemini-mcp-tool by jamubc · ⭐ 2.3k

    MCP server that enables AI assistants to interact with Google Gemini CLI, leveraging Gemini's massive token wi

  • mcp-memory-service by doobidoo · ⭐ 2.0k

    Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowl

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Frequently Asked Questions

What is maestro-flow?

maestro-flow is Intent-driven workflow orchestration for multi-agent AI development — adaptive lifecycle engine, self-reinforcing knowledge graph, and visual dashboard for Claude Code, Gemini, Codex & more. It is categorized as a MCP Server with 556 GitHub stars.

What programming language is maestro-flow written in?

maestro-flow is primarily written in TypeScript. It covers topics such as ai-agents, claude-code, cli.

How do I install or use maestro-flow?

You can find installation instructions and usage details in the maestro-flow GitHub repository at github.com/catlog22/maestro-flow. The project has 556 stars and 68 forks, indicating an active community.

What are the best alternatives to maestro-flow?

The top alternatives to maestro-flow on Agent Skills Hub include Overture, octocode, sudocode. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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:

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