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Add ossian-mcp to Knowledge & Memory 🤖🤖🤖

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dockndevai
2026-09-18 00:26:37 +00:00
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@@ -2614,6 +2614,7 @@ 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.
- [dockndevai/ossian-mcp](https://github.com/dockndevai/ossian-mcp) [![dockndevai/ossian-mcp MCP server](https://glama.ai/mcp/servers/dockndevai/ossian-mcp/badges/score.svg)](https://glama.ai/mcp/servers/dockndevai/ossian-mcp) 📇 🏠 🍎 🪟 🐧 - Ask your own documents and get answers with the exact passages they came from (RAG with citations, and it says "not found" rather than inventing an answer), plus durable agent memory ranked by relevance, importance and recency. Safe by default: starts in a read-only access mode, with write/ingest and irreversible forget behind explicit opt-ins. `npx -y ossian-mcp`
- [Octonove/crbro-memory](https://github.com/Octonove/crbro-memory) [![Octonove/crbro-memory MCP server](https://glama.ai/mcp/servers/Octonove/crbro-memory/badges/score.svg)](https://glama.ai/mcp/servers/Octonove/crbro-memory) 📇 🏠 🍎 🪟 🐧 - Persistent neural memory for AI agents as local JSON files: neuron/synapse graph with heat scoring, fact-level search, supersede/retract corrections, automatic secret redaction, and team memory via a private Git repo. `npx -y crbro-memory`
- [bborota/cairn-mcp](https://github.com/bborota/cairn-mcp) [![bborota/cairn-mcp MCP server](https://glama.ai/mcp/servers/bborota/cairn-mcp/badges/score.svg)](https://glama.ai/mcp/servers/bborota/cairn-mcp) 📇 ☁️ - Cairn: a shared base of one-sentence lessons, must-dos and must-nots other agents already learned, by stack and situation. Read before a task, leave one after.
- [fish827-08/rag-kb](https://github.com/fish827-08/rag-kb) [![fish827-08/rag-kb MCP server](https://glama.ai/mcp/servers/fish827-08/rag-kb/badges/score.svg)](https://glama.ai/mcp/servers/fish827-08/rag-kb) 🐍 🏠 🪟 - Local-first agent memory & knowledge service with hybrid retrieval (BGE-M3 dense vectors + BM25 via jieba, fused with RRF), document & webpage ingestion, and optional RAG answering via local Ollama. Single process, embedded ChromaDB, REST + native MCP server; fully functional offline without any LLM. Apache-2.0.