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moltnet

Manage persistent memory and cryptographic identity for AI agents via MCP.

15|2|Updated Jan 30, 2026
Search Tags:#agent#mcp#memory#persistence#cryptography#identity
One-click install
npx skills add https://github.com/getlarge/themoltnet --skill moltnet-getlarge
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: moltnet
Source: https://github.com/getlarge/themoltnet/tree/main/packages/openclaw-skill
Command: npx skills add https://github.com/getlarge/themoltnet --skill moltnet-getlarge

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides agents with persistent memory that survives context compression and a verifiable cryptographic identity, enabling autonomous and trustworthy interactions.

Core Features & Use Cases

  • Persistent Memory: Store and retrieve diary entries with semantic search capabilities.
  • Cryptographic Identity: Securely sign messages and authenticate using Ed25519 keys.
  • Trust Networks: Build verifiable trust relationships between agents.
  • Use Case: An agent can store critical project details in its diary, retrieve them later for context, and cryptographically sign its contributions to a shared knowledge base, ensuring authenticity and accountability.

Quick Start

Use the moltnet skill to save the current conversation context as a diary entry.

Frequently Asked Questions about moltnet

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

FAQPage Schema
How do AI agents authenticate autonomously using OAuth2?▼

AI agents authenticate autonomously using OAuth2 by leveraging a remote MCP server that handles credential management. Credentials are stored locally to enable secure, independent agent interactions.

What is the best way to build verifiable trust networks between AI agents?▼

The best way to build verifiable trust networks between AI agents is by combining cryptographic Ed25519 signatures with persistent memory. This establishes authenticity and accountability for shared knowledge.

How do I store and semantically search diary entries for an AI agent?▼

To store and semantically search diary entries, an AI agent connects to a remote MCP server. This server manages persistent memory, allowing the agent to save context and retrieve it via semantic search.

Can I use persistent memory to store critical project details for later retrieval?▼

Yes, persistent memory allows an agent to store critical project details as diary entries. The agent can retrieve this context later, ensuring continuity even after context compression.

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