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The m_flow MCP server was last committed 23d ago and has 8 contributors. Issue health: 46% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

m_flow MCP Server

Name: FlowElement-xinliuyuansu/m_flow
Rating: 3.4 (1 reviews)
Author: FlowElement-xinliuyuansu

FlowElement-xinliuyuansu/m_flow

Score: 59.8 Rank #5768 Search & RAG

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A bio-inspired cognitive memory engine — a new paradigm for Graph RAG.

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Overview

FlowElement-xinliuyuansu/m_flow is a Python tool licensed under Apache-2.0. A bio-inspired cognitive memory engine — a new paradigm for Graph RAG. Topics: agent-memory, agentic-ai, ai-reasoning, episodic-memory, graph-database, knowledge-graph, llm, long-term-memory, mcp, memory-engine, python, rag, semantic-memory, vector-search.

Ranked #5768 out of 24840 indexed tools.

Has 4,508 GitHub stars.

Ecosystem

Python Apache-2.0

agent-memoryagentic-aiai-reasoningepisodic-memorygraph-databaseknowledge-graphllmlong-term-memorymcpmemory-enginepythonragsemantic-memoryvector-search

Score Breakdown

Stars 15% 4,508

4,508 stars → well-known project

Freshness 25% 23d ago

Last commit 23d ago → recently updated

Issue Health 25% 46%

11/24 issues closed → many open issues

Contributors 10% 8

8 contributors → small team

Dependents 25% 2

2 dependents → few downstream users

npm Downloads N/A

PyPI Downloads N/A

Forks 259

Description Good

License Apache-2.0

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

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Issue Health high impact

You have 13 open vs 11 closed issues — triaging stale issues improves health

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Details

Stars: 4,508
Forks: 259
Open Issues: 13
Closed Issues: 11
Contributors: 8
Dependents: 2
Language: Python
License: Apache-2.0
Last Commit: 23d ago

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topic:mcp

From the README

<div align="center">

# M-flow

**RAG matches chunks. GraphRAG structures context. M-flow scores evidence paths.**

Retrieval through reasoning and association — M-flow operates like a cognitive memory system.

[m-flow.ai](https://m-flow.ai) ·
[flowelement.ai](https://flowelement.ai) ·
[Quick Start](#quick-start) ·
[Architecture](docs/RETRIEVAL_ARCHITECTURE.md) ·
[Examples](examples/) ·
[OpenClaw Skill](https://clawhub.ai/flowelement-alexunbridled/mflow-memory) ·
[Contact](mailto:[email protected])

</div>

---

## What is M-flow?

The real shift is not whether a system builds a graph, but what the graph is allowed to do at retrieval time.

### Graph topology encodes relevance.

In most RAG systems, retrieval is still dominated by similarity: the query is embedded, textual units are ranked by vector distance, and structure—if present—mainly helps organize, summarize, or expand context. Many GraphRAG systems add entities, relations, and community structure, but the graph often re

Read full README on GitHub →