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Memory Snapshot Service

Save and retrieve AI agent conversation states via HTTP API endpoints.

Updated Feb 10, 2026
Search Tags:#AI agent#context persistence#context continuity#memory snapshot#USDC payment
One-click install
npx skills add https://github.com/masteringpants-dev/memory-snapshot-service --skill memory-snapshot-service
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Memory Snapshot Service
Source: https://github.com/masteringpants-dev/memory-snapshot-service/tree/main
Command: npx skills add https://github.com/masteringpants-dev/memory-snapshot-service --skill memory-snapshot-service

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires fastapi, uvicorn, pydantic, httpx, circle-web3-sdk-util, python-dotenv, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of AI agent amnesia by allowing you to save and retrieve conversation states for agents, ensuring continuous context awareness.

Core Features & Use Cases

  • Persistent Context: Save conversation states to prevent information loss during context windows, session restarts, or model switches.
  • USDC Micro-Payments: Utilize micro-payments to save and retrieve state, offering flexibility and control.
  • API Endpoints: Offers endpoints to save, retrieve, list, and health check the memory snapshots. Includes endpoints like POST /snapshot/save and GET /snapshot/{id}.

Quick Start

Run the Memory Snapshot Service and save a snapshot with the save_snapshot endpoint, providing necessary parameters like agent_id and content.

Frequently Asked Questions about Memory Snapshot Service

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

FAQPage Schema
How do I persist AI agent context across session restarts?▼

Memory snapshots save conversation states so AI agents maintain continuous context awareness across session transitions, model changes, or context window compression. The service provides HTTP API endpoints like POST /snapshot/save to store state and GET /snapshot/{id} to retrieve it.

How do I save and retrieve AI agent memory snapshots?▼

Run the service and send a POST request to the /snapshot/save endpoint with parameters like agent_id and content to save a snapshot. Retrieve saved states using the GET /snapshot/{id} endpoint, or list existing snapshots to manage your agent's memory.

Does the memory snapshot service require USDC payments to save context?▼

Yes, saving and retrieving conversation states requires USDC micro-payment validation. This mechanism controls access to the memory snapshot operations, ensuring context persistence is managed through validated micro-transactions.

Can I use Google Drive as a persistent backend for AI agent memory?▼

Yes, the service operates with HTTP-based API endpoints that leverage either in-memory storage or a persistent backend like Google Drive. This allows you to store and retrieve agent conversation states beyond temporary memory limits.

What are the limitations of in-memory storage for AI agent context continuity?▼

In-memory storage is volatile and loses conversation states if the FastAPI service restarts. To ensure continuous context awareness across session transitions or model switches, a persistent backend like Google Drive is required for reliable memory snapshot retention.

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