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memphis-brain

Integrate persistent semantic memory into OpenClaw agents via IPFS.

1|Updated Feb 17, 2026
Search Tags:#semantic search#agent#memory#journaling#openclaw#ipfs#memphis
One-click install
npx skills add https://github.com/elathoxu-crypto/memphis --skill memphis-brain
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memphis-brain
Source: https://github.com/elathoxu-crypto/memphis/tree/main/skills/memphis-brain
Command: npx skills add https://github.com/elathoxu-crypto/memphis --skill memphis-brain

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires memphis-cli, ollama, nomic-embed-text, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides OpenClaw agents with persistent, semantic memory, enabling them to retain context and learn over time.

Core Features & Use Cases

  • Persistent Memory: Agents remember across sessions and maintain a continuous knowledge base.
  • Semantic Recall: Find relevant context using semantic search and embeddings.
  • Journaling: Capture insights, decisions, and learnings in a structured journal.
  • Multi-Agent Sync: Share memory and knowledge across multiple agents using IPFS.
  • Use Case: For an agent involved in project management, this Skill can help track decisions, learn from past projects, and share knowledge with other agents in the network.

Quick Start

Initialize a new agent by running the following command:

bash ~/.openclaw/workspace/skills/memphis-brain/scripts/agent-init.sh

Frequently Asked Questions about memphis-brain

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I add persistent memory to AI agents for context retention across sessions?▼

Persistent memory for AI agents is added by integrating a local-first brain using semantic search and embeddings, enabling agents to retain context and maintain a continuous knowledge base across sessions.

How does semantic search work for agent memory and journaling?▼

Semantic search for agent memory works by generating embeddings of captured journal entries and decisions, allowing agents to find and recall relevant context based on meaning rather than exact keyword matches.

Do I need Ollama and Memphis CLI to set up local-first semantic memory?▼

Yes, setting up local-first semantic memory requires the Memphis CLI and Ollama runtime to handle memory management and generate text embeddings for the agent's knowledge base.

Can multiple agents share memory and knowledge using IPFS?▼

Multiple agents can share memory and knowledge using IPFS, which enables multi-agent collaboration by synchronizing journal entries, decisions, and learned context across the network.

How do I initialize an OpenClaw agent with persistent memory?▼

To initialize an OpenClaw agent with persistent memory, run the agent initialization bash script located in the workspace skills directory to configure the local-first brain environment.

What are the limitations of using a local-first brain for agent memory management?▼

Limitations of local-first brain memory management include reliance on local hardware resources for running the Ollama runtime and embedding models, and dependency on IPFS availability for multi-agent knowledge synchronization.

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