by RyjoxTechnologies · MCP Server · ★ 475
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Octopoda The open-source memory operating system for AI agents. Give your agents persistent memory, loop detection, audit trails, and real-time observability. Everything works automatically once you create an agent. []() Track latency, error rates, memory usage, and health scores per agent. Browse every memory, inspect version history, and see exactly how an agent's knowledge changed over time. Quick Start That's it. Your agent now has persistent memory, loop detection, crash recovery, and an audit trail. Everything runs automatically in the background. Memory survives restarts, crashes, and deployments. Store and retrieve memories when you need to: python agent.remember("key", "value") agent.reca
| Stars | 475 |
| Forks | 79 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 72.7064379841469/100 |
| Open Issues | 13 |
| Last Updated | 2026-07-15 |
| Created | 2026-04-02 |
| Platforms | mcp, python |
| Est. Tokens | ~15k |
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Octopoda-OS is The open-source memory and observability layer for AI agents — persistent memory, loop detection, hash-chained audit trails, and a live dashboard, automatic on pip install.. It is categorized as a MCP Server with 475 GitHub stars.
Octopoda-OS is primarily written in Python. It covers topics such as agent-framework, ai-agents, ai-memory.
You can find installation instructions and usage details in the Octopoda-OS GitHub repository at github.com/RyjoxTechnologies/Octopoda-OS. The project has 475 stars and 79 forks, indicating an active community.
The top alternatives to Octopoda-OS on Agent Skills Hub include mcp-memory-service, antigravity-workspace-template, DeepMCPAgent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.