Team Shared Memory With Role Based Access

via “team shared memory with role-based access”

AI code snippet manager with context capture.

Unique: Extends personal context capture to team level, enabling shared memory of code, documents, and activity across team members with role-based access control. Syncs via Pieces Drive (cloud) but mechanism (real-time vs eventual consistency) is undocumented.

vs others: Shares context automatically (unlike manual documentation or wikis), integrates with personal memory (unlike separate team knowledge bases), and supports role-based access (unlike flat-permission sharing).

via “multi-cube and multi-user pattern support with shared memory access”

AI memory OS for LLM and Agent systems(moltbot,clawdbot,openclaw), enabling persistent Skill memory for cross-task skill reuse and evolution.

Unique: Implements selective memory sharing across isolated cubes with configurable access policies, enabling collaboration without breaking tenant isolation — unlike monolithic memory systems, MemOS supports federated memory access patterns.

vs others: Enables multi-agent collaboration with memory isolation; adds complexity and query latency for shared memory access, but critical for team-based agent deployments.

via “multi-participant memory isolation and access control”

Hello HN! I built collabmem, a simple memory system for long-term collaboration between humans and AI assistants. And it's easy to install, just ask Claude Code: Install the long-term collaboration memory system by cloning https://github.com/visionscaper/collabmem to a te

Unique: Implements fine-grained access control for collaborative memories, enabling selective sharing of context across participants while maintaining isolation of sensitive information

vs others: Provides participant-aware memory filtering unlike shared conversation logs, and enables selective context sharing for multi-team collaborations

via “multi-user memory isolation with role-based access control”

Long-term memory for AI Agents

Unique: Implements user-scoped memory isolation with role-based access control, automatically filtering memory queries based on authenticated user context and explicit permission policies, preventing cross-user data leakage

vs others: More comprehensive than simple user_id filtering (which requires manual query construction) but less sophisticated than full attribute-based access control systems, suitable for SaaS but may require custom extensions for complex enterprise policies

via “multi-session context sharing”

A recreation of the Supermemory MCP with all features of the Supermemory API

Unique: The centralized memory store for multi-session sharing is designed to minimize context loss, which is often a challenge in traditional implementations.

vs others: More effective than alternatives that require manual context transfer between sessions.

via “team memory sharing and collaboration”