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Merge pull request #9349 from TanmayKnight/add-memini

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Add memini to Knowledge & Memory
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Frank Fiegel
2026-07-22 12:46:01 +02:00
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@@ -2040,6 +2040,7 @@ Connect AI agents to industrial equipment, machinery, and operational technology
Persistent memory storage using knowledge graph structures. Enables AI models to maintain and query structured information across sessions.
- [lumayapartners/memini](https://github.com/lumayapartners/memini) [![lumayapartners/memini MCP server](https://glama.ai/mcp/servers/lumayapartners/memini/badges/score.svg)](https://glama.ai/mcp/servers/lumayapartners/memini) 📇 🏠 🍎 🪟 🐧 - Local-first project memory and guardrails for coding agents. Records failed attempts, fragile files, and decisions per repo; warns the agent before it repeats a recorded mistake. `npx -y memini mcp`
- [soolaugust/0CompactMem](https://github.com/soolaugust/0CompactMem) [![soolaugust/0CompactMem MCP server](https://glama.ai/mcp/servers/soolaugust/0CompactMem/badges/score.svg)](https://glama.ai/mcp/servers/soolaugust/0CompactMem) 🐍 🏠 🍎 🪟 🐧 - Persistent memory MCP server with OS-style demand paging, kswapd-style eviction, and mlock pinning. Multi-agent shared SQLite store with BM25 + FTS5 retrieval, importance scoring, and capacity-aware reclaim. 5 tools: `memory_lookup`, `pin_memory`, `unpin_memory`, `memory_stats`, `list_pinned`. `uvx --from git+https://github.com/soolaugust/0CompactMem memory-os`
- [a2cr/a2cr](https://github.com/a2cr/a2cr) [![a2cr/a2cr MCP server](https://glama.ai/mcp/servers/a2cr/a2cr/badges/score.svg)](https://glama.ai/mcp/servers/a2cr/a2cr) 🐍 ☁️ 🏠 🍎 🪟 🐧 - MCP server for AI-agent handoffs. Saves client-encrypted WorkBaton checkpoints and WorkStash notes so Codex, Claude Code, Roo Code, and other MCP clients can resume work without passing full chat history.
- [ahmetakyurt/zipmem-mcp](https://github.com/ahmetakyurt/zipmem-mcp) [![ahmetakyurt/zipmem-mcp MCP server](https://glama.ai/mcp/servers/ahmetakyurt/zipmem-mcp/badges/score.svg)](https://glama.ai/mcp/servers/ahmetakyurt/zipmem-mcp) 📇 🏠 - Local-first long-term memory for terminal AI agents (Claude Code et al.) via Anchored Compacting. Stores blueprints, code anchors (file→line→concept), and distilled lessons in a single JSON under `.zipmem/`, restoring full cross-session project context at near-zero token cost. No DB, no API keys, no embeddings. `npx zipmem-mcp`