External Memory Providers: Zero-Downtime Context Compaction for AI Agents

Every AI agent has a dirty secret: when its context window fills up, it has to stop and think about what to forget. In OpenClaw (and most agent frameworks), this happens through synchronous in-band compaction . The agent pauses, sends its entire context to an LLM for summarization, replaces the original with the summary, and resumes. During that 30-60 second window? The agent is completely unresponsive. For a personal assistant, that's annoying. For customer support, financial services, or healthcare agents? It's a dealbreaker. GitHub issue #49233 proposes a solution: an External Memory Provider API that enables zero-downtime compaction. The Problem: Compaction Is a Mini-Outage Here's what happens today: Agent stops responding Full context sent to LLM for summarization (~30-60s) Summary replaces original context (information loss) Agent resumes with degraded memory The core issue: it's synchronous and in-band . The agent can't serve the user AND compress its memory simultaneously. The