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memory extension for OpenClaw — Turbopuffer vectors + DynamoDB knowledge graph","maintainers":[{"name":"kevupton","email":"kevin@upton.tech"},{"name":"sam-alfe","email":"sam@alfe.ai"}],"readme":"# `@alfe.ai/openclaw-memory-cloud`\n\nOpenClaw's private, per-agent cloud-memory plugin. It captures bounded\nconversation windows, recalls escaped context, and exposes tools for vector\nmemory and the per-agent knowledge graph through the Alfe Agent API.\n\n## Safety model\n\nLive capture state is isolated by the canonical OpenClaw `sessionKey`; there is\nno process-wide current session. Flushes for one session are serialized so the\nmemory service's high-water mark cannot observe a later batch first. A\nstrictly monotonic, owner-only epoch fences daemon restarts. If that state\ncannot be secured, auto-capture is disabled while recall and explicit tools\nremain available.\n\n`memory_forget` is a two-step operation: the first call previews up to five\ncurrent matches and the second must confirm those exact IDs in the same order.\n`memory_learn` accepts bounded inline text or a regular, non-symlink file under\nthe configured runtime workspace. Service responses are normalized before\nthey reach the model, and recalled context is escaped and capped at 16 KiB.\n\n## Development\n\n```bash\npnpm --filter @alfe.ai/openclaw-memory-cloud lint\npnpm --filter @alfe.ai/openclaw-memory-cloud typecheck\npnpm --filter @alfe.ai/openclaw-memory-cloud test\npnpm --filter @alfe.ai/openclaw-memory-cloud build\n```\n\nThe package publishes ESM and CJS entrypoints. The OpenClaw loader uses the\ndefault-only `./plugin` export. Keep the tool\ncatalog and configuration bounds aligned with `openclaw.plugin.json` and the\nmemory service's agent routes.\n\nPart of [Alfe](https://alfe.ai). See the [documentation](https://docs.alfe.ai)\nfor platform setup.\n","readmeFilename":"README.md"}