Long-running fleet orchestration and memory infrastructure for AI agents. Enables persistent context, shared memory, task execution, and governed coordination across multi-agent systems.
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Updated
Oct 22, 2026 - Python
Long-running fleet orchestration and memory infrastructure for AI agents. Enables persistent context, shared memory, task execution, and governed coordination across multi-agent systems.
Multi-agent memory governance demo using Caura + OpenClaw. Three agents (Sales, Legal, Admin) share one memory backend with hard fleet boundaries enforced at the query layer. Shows scoped writes, blocked recall, cross-fleet synthesis, and conflict detection.
Local-first memory governance for AI agents: shared, reviewable, auditable memory via SQLite and MCP.
The AI agent memory layer you can audit — local-first memory governance for AI agents: citations, trust policies, trace receipts, rollback. SQLite, sidecar-first, OpenClaw plugin.
Durable, repo-native project memory for coding agents, without context bloat.
Governed memory for long-lived coding agents. Trust, provenance, conflict detection. Local-first.
Git-backed, conflict-safe memory authority for AI agents via MCP (Model Context Protocol).
面向 Coding Agent 的本地共享记忆层:跨 Agent 共享验证知识、零噪声召回与 LFHV 可逆遗忘。
Trust-aware memory for AI agents: evidence-backed recall, deterministic verdicts, self-inspection, and a tamper-evident local ledger.
Local-first read-only tools for agent context, memory, and governance evaluation before agents act.
forgetted is a Python library for selective memory governance in AI agents: a context-managed window where the agent keeps full read access but its writes to memory files, session logs, deliverables, and an optional vector store vanish and are cleaned up on exit.
Experimental pre-1.0 multi-agent memory governance/control plane
Sanitized starter kit for Hermes Agent memory, skill, cron, and Kanban governance
开源 AI Agent 治理技能库:109 个零依赖技能,让每个 AI 输出有籍·有证·有门禁。覆盖 AI 治理 / Agent 安全 / 合规自动化 / 记忆治理,适配 Claude Code · Codex · Cursor · WorkBuddy。
Markdown-first, local-first memory architecture for AI agents with lifecycle, distillation, and human-readable memory artifacts.
Governed cognition substrate for AI engineering agents: mission envelopes, evidence-bound belief/plan graphs, quarantined memory, model-role review, sentinel checks, and BlackFox handoffs under human authority.
Trusted enterprise memory governance for RAG and AI agents
Technemachina Daemon — an independent local-first AI research system for governed memory, provenance, auditable decisions, and human authority.
Local-first, reviewable memory layer for Codex with MCP, lifecycle hooks, and memory governance.
Local-first cognition governance for long-running AI agents: compact world state, evidence weighting, conflict detection, and hook-friendly memory control.
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