How do I install the Mflow Memory skill?

Run npx skillmds@latest add flowelement-xinliuyuansu/mflow-memory in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Mflow Memory safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Mflow Memory?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Mflow Memory free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Mflow Memory?

flowelement-xinliuyuansu (@flowelement-xinliuyuansu) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Mflow Memory by flowelement-xinliuyuansu

Name: Mflow Memory
Author: flowelement-xinliuyuansu

Mflow Memory

Long-term memory engine for OpenClaw agents using M-flow knowledge graphs. Stores conversations as structured episodic memories and retrieves via graph-routed search. Use when the agent needs to remember past conversations, recall user preferences, or maintain context across sessions. Requires Docker.

File contents

M-flow Memory

Gives your agent persistent long-term memory powered by M-flow's cognitive memory engine.

Setup

Run once:

bash ~/.openclaw/skills/mflow-memory/scripts/setup.sh

This starts the M-flow MCP server and registers it with OpenClaw.

Memory Strategy

Follow these rules for every conversation:

Before answering, silently call search with the user's question to check for relevant memories. If memories are found, use them as context.
At the end of a conversation that contained meaningful information (decisions, facts, preferences, plans — not greetings or small talk), call save_interaction with the conversation content.
When the user explicitly asks you to remember something ("remember that I'm allergic to peanuts", "note that the deadline is Friday"), call save_interaction immediately — do not wait until the end of the conversation.
When the user says "remember", "last time", "before", "previously", or references past events, always call search first.
Do not store trivial exchanges, repeated information, or content the user asks you to forget.

Available Tools (via MCP)

After setup, these tools are automatically available:

save_interaction — Store a conversation as memory (preferred for dialogue)
search — Search memories by natural language query
query — Ask a question and get an answer grounded in memories
memorize — Build knowledge graph from previously added data
ingest — One-step store + memorize (for documents)
list_data — List stored datasets
delete — Remove specific memories
memorize_status — Check if memorization is still processing
prune — Reset all memory

Troubleshooting

# Check if M-flow is running
bash ~/.openclaw/skills/mflow-memory/scripts/status.sh

# Restart
docker restart mflow-memory

# View logs
docker logs mflow-memory --tail 20

# Complete removal
bash ~/.openclaw/skills/mflow-memory/scripts/teardown.sh

---name: mflow-memorydescription: Long-term memory engine for OpenClaw agents using M-flow knowledge graphs. Stores conversations as structured episodic memories and retrieves via graph-routed search. Use when the agent needs to remember past conversations, recall user preferences, or maintain context across sessions. Requires Docker.---# M-flow MemoryGives your agent persistent long-term memory powered by M-flow's cognitive memory engine.## SetupRun once:```bashbash ~/.openclaw/skills/mflow-memory/scripts/setup.sh```This starts the M-flow MCP server and registers it with OpenClaw.## Memory StrategyFollow these rules for every conversation:1. **Before answering**, silently call `search` with the user's question to check for relevant memories. If memories are found, use them as context.2. **At the end of a conversation** that contained meaningful information (decisions, facts, preferences, plans — not greetings or small talk), call `save_interaction` with the conversation content.3. **When the user explicitly asks you to remember something** ("remember that I'm allergic to peanuts", "note that the deadline is Friday"), call `save_interaction` immediately — do not wait until the end of the conversation.4. **When the user says** "remember", "last time", "before", "previously", or references past events, always call `search` first.5. **Do not store** trivial exchanges, repeated information, or content the user asks you to forget.## Available Tools (via MCP)After setup, these tools are automatically available:- `save_interaction` — Store a conversation as memory (preferred for dialogue)- `search` — Search memories by natural language query- `query` — Ask a question and get an answer grounded in memories- `memorize` — Build knowledge graph from previously added data- `ingest` — One-step store + memorize (for documents)- `list_data` — List stored datasets- `delete` — Remove specific memories- `memorize_status` — Check if memorization is still processing- `prune` — Reset all memory## Troubleshooting```bash# Check if M-flow is runningbash ~/.openclaw/skills/mflow-memory/scripts/status.sh# Restartdocker restart mflow-memory# View logsdocker logs mflow-memory --tail 20# Complete removalbash ~/.openclaw/skills/mflow-memory/scripts/teardown.sh```

Frequently asked questions