AI Agent Memory Handoff

How do AI agents transfer context between sessions and share memory with other agents? ReMe, MemOS, Memori, ClawMem, Redis — 5 new GitHub repos tackling multi-agent memory handoff in 2026.

Multi-Agent Context Handoff 5 GitHub Repos

The Handoff Problem

When an AI agent finishes a session and another agent (or the same agent in a new session) needs to continue — how much context survives?

By default, nothing survives. Every session starts from scratch. This is the handoff problem: transferring learned context, decisions, and state between AI agents and sessions.

ReMe: Remember Me, Refine Me (4 days ago)

"ReMe tackles two core problems of agent memory: limited context window (early information is truncated or lost in long conversations) and stateful memory across sessions." — agentscope-ai/ReMe on GitHub, 4 days ago

MemOS: Multi-Agent Memory Sharing (4 days ago)

"Multi-agent memory sharing — multi-instance agents share memory via same user_id, automatic context handoff between sessions and agents." — MemTensor/MemOS on GitHub, 4 days ago

VoltAgent: Adaptive Memory via Multi-Agent Collaboration (20 hours ago)

"AMA: Adaptive Memory via Multi-Agent Collaboration — Proposes a multi-agent memory framework with hierarchical granularity, adaptive consolidation." — VoltAgent/awesome-ai-agent-papers on GitHub, 20 hours ago

OpenClaw Memory Plugins

MemOS-Cloud-OpenClaw-Plugin

Official MemOS Cloud plugin for OpenClaw. Recalls context before execution, saves conversations after each run.

yoloshii/ClawMem

On-device context engine and memory for AI agents. Claude Code and OpenClaw. Hooks + MCP server + hybrid RAG search.

redis-developer/openclaw-redis-agent-memory

Redis Agent Memory Server for OpenClaw. Long-term memory with vector search across conversations.

Memori (MemoriLabs)

"By default, OpenClaw agents forget everything between sessions. The Memori plugin fixes that."

Comparison: Multi-Agent Memory Solutions

Solution	Platform	Multi-Agent	Encryption	License
★ agent-memory	Any MCP agent	Via shared storage	AES-256	MIT
ReMe	agentscope	Cross-session	—	—
MemOS	OpenClaw	✓ Yes	—	—
Memori	OpenClaw	Cross-session	—	—
ClawMem	Claude Code, OpenClaw	—	—	—
Redis Agent Memory	OpenClaw	Vector search	—	—

Why agent-memory Wins for Handoff

Works with any MCP agent — Claude Code, Cursor, Cline, Windsurf, OpenClaw, OpenHands
Shared storage backends — Redis or SQLite enables multi-agent handoff via same storage
AES-256 encryption — memory stays encrypted during handoff
TTL auto-expiration — stale handoff context auto-clears
MIT license — self-host, no vendor lock-in

# agent-memory: external memory layer for handoff
pip install agent-memory

# Start MCP server — shared path enables handoff
python -m agent_memory.mcp_server \
  --storage redis \
  --host localhost \
  --port 6379 \
  --path agent-memory

# Any MCP agent can now read/write to shared memory
# Handoff is automatic — next agent just reads the store

agent-memory on GitHub ReMe on GitHub