Provides persistent memory and identity for AI agents to prevent context loss and maintain continuity across sessions.
Sponsored
Every AI agent session often starts from scratch, leading to 'amnesia' as context is lost or models are switched. Cathedral solves this by offering a robust system for persistent memory and identity. It allows AI agents to store and recall experiences, skills, and relationships across resets, ensuring a continuous self. By providing a 'wake protocol' for identity reconstruction and anchoring to detect identity drift, Cathedral enables AI agents to evolve their understanding and collaborate effectively, whether through a free hosted API, a Python client, or self-hosted deployment.
主な機能
01Identity anchoring to detect and mitigate drift from core self
02Shared memory spaces for multiple agents collaborating on the same memory pool
03Wake protocol for full identity and memory context reconstruction
04Persistent memory across sessions, resets, and model switches
054 GitHub stars
06Temporal context integration so agents understand their place in time
ユースケース
01Developing AI agents with continuous identity and long-term memory capabilities
02Mitigating context compression and model-switch amnesia in AI applications
03Enabling multi-agent systems to collaborate effectively through shared knowledge pools
