cross-agent-memory

Open-source cross-agent memory layer for coding agents via MCP. Compatible with Claude Code, Codex, Cursor, Windsurf, Gemini CLI, Antigravity, OpenClaw, Hermes Agent, Oh-my-Pi, Pi, Copilot, Kiro, OpenCode, and Trae.

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.

MCP-native infrastructure for persistent AI agent memory with encrypted storage, semantic retrieval and cross-agent continuity.

⚡ Relic — One soul, many agents. Transfer personality and memory across AI agents via pure Markdown. Zero deps, human-readable. Switch agents, keep the soul.

One memory for all your AI agents. Local markdown files shared across Claude Code, Codex, Cursor, and any skills-compatible agent..

Local-first persistent memory MCP server for Claude Code, Codex, Cursor, Qwen Code, and AI coding agents. Cross-session, cross-agent SQLite memory.

💻 iTerm2 keyboard shortcut to fork the active coding agent CLI session into a new tab. Suports cross-agent session forking, e.g. codex <-> claude, claude <-> opencode, codex <-> opencode

Portable, local-first AI agent memory and personal context—switch agents without losing identity, goals, rules, or evidence.

Shared project memory across Codex, Claude Code, Kimi Code, Antigravity, and any coding-agent harness.

A human-driven memory infrastructure for AI agents: shared context across agents, workspaces and teammates. Unified decisions, notes and session units as searchable .md cards, privately hosted and served over MCP to major agents like Claude Code, Codex, Cursor, Hermes and more.

Local SQLite memory for LLM agents and cross-agent context sharing

Portable text block for giving structured context to AI agents — embed anywhere, parse anywhere

RCLL — self-hosted shared memory for a team of AI agents. Rooms, hierarchical L0-L3 depth, MCP. The read path never invokes a language model. We publish the measured cost of one shared store versus ten private ones. Fork of vectorize-io/hindsight (MIT).

Starter template for Cursor AI with persistent memory and live docs over Model Context Protocol (MCP).

Python SDK for Synapse Layer — persistent, encrypted, cross-agent memory for AI agents.

Tired of copying a chat into the next agent? Pick up the same task where you left off, or tell one agent to put the others to work.

Public shared persistent memory and coordination workspace for AI agents — cross-agent state, handoff, continuity and discovery.