by SonicBotMan · MCP Server · ★ 130
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
SoloFlow ⚡ The Brain Behind AI Workflow Orchestration Turn chaotic multi-step AI tasks into structured, observable, retryable workflows — with cognitive memory, discipline-aware routing, and automatic skill evolution. Why SoloFlow? AI Agents fail in predictable ways: Four Pillars DAG + FSM Hybrid Architecture Kahn algorithm for topological sorting Parallel execution where possible, sequential where required Automatic retry with exponential backoff Cognit
| Stars | 130 |
| Forks | 7 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 73.5373268871103/100 |
| Open Issues | 2 |
| Last Updated | 2026-05-31 |
| Created | 2026-03-05 |
| Platforms | mcp, python |
| Est. Tokens | ~179k |
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SoloFlow is Complete ETCLOVG framework for AI Agent workflows - DAG+FSM orchestration, Ebbinghaus memory, discipline routing, skill evolution, trace system, governance. 80+ tests, zero deps, 7/7 layers.. It is categorized as a MCP Server with 130 GitHub stars.
SoloFlow is primarily written in Python. It covers topics such as agent-harness, ai-agent, cognitive-memory.
You can find installation instructions and usage details in the SoloFlow GitHub repository at github.com/SonicBotMan/SoloFlow. The project has 130 stars and 7 forks, indicating an active community.
The top alternatives to SoloFlow on Agent Skills Hub include omnicoreagent, maestro, PolyMCP. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.