FlowElement-ai

FlowElement-ai / m_flow

Public

M-Flow — Memory-augmented knowledge graph framework for AI agents

m-flow.ai
43
6
100% credibility
Found Apr 03, 2026 at 43 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

M-flow is a cognitive memory engine that structures knowledge into layered hierarchies for AI agents to retrieve via reasoning and relationships instead of simple similarity matching.

How It Works

1
🔍 Discover M-flow

You hear about M-flow, a smart memory helper that lets AI remember and connect ideas like a real mind.

2
🚀 Quick setup

Run one simple command to get everything running on your computer with a friendly guide.

3
🔑 Link your AI brain

Enter your AI service details once, and M-flow connects so it can think and remember deeply.

4
📚 Feed your knowledge

Upload documents, notes, or conversations, and watch M-flow organize them into smart layers.

5
💭 Ask natural questions

Type everyday questions, and M-flow reasons through connections to give precise, thoughtful answers.

✨ AI remembers perfectly

Your AI now recalls details with context and associations, making conversations smarter and more reliable.

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AI-Generated Review

What is m-flow?

M-flow is a Python memory-augmented knowledge graph framework for AI agents. It distills docs, chats, or workflows into a Cone Graph—layered from episodes to entities—and retrieves via relationship reasoning, not vector similarity. Users ingest 50+ file formats with `mflow add` or API, memorize, then query via CLI/Web UI for precise, multi-hop recall.

Why is it gaining traction?

Beats Mem0 on benchmarks (76% vs 67% LLM-judge accuracy, especially temporal/multi-hop), with 5 modes like episodic/cypher search across Neo4j, pgvector, or Chroma. Docker quickstart launches full stack (API+UI) in minutes; LLM-agnostic (OpenAI to Ollama) and MCP server hooks into IDEs. Devs dig the graph viz and no-RAG reasoning flow.

Who should use this?

Agent builders crafting persistent-memory bots—like support systems recalling user history or research tools chaining facts across convos. Python teams replacing context windows or basic RAG in multi-turn apps, especially with procedural knowledge like workflows.

Verdict

Promising prototype: 43 stars and 1% credibility signal early days, but 963 tests pass, docs shine, and quickstart proves polish. Spin it up for agent experiments; scale cautiously sans battle-tested prod use.

(187 words)

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