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Dev tools · February 17, 2026

PM

Persistent memory for Claude Code with self-hosted Qdrant and Ollama

I built an MCP server that gives Claude Code long-term memory across sessions, backed by infrastructure you control. Every Claude Code session starts from zero, no memory of previous sessions. This server uses mem0ai as a library and exposes 11 MCP tools for storing, searching, and managing memories. Qdrant handles vector storage, Ollama runs embeddings locally (bge-m3), and Neo4j optionally builds a knowledge graph. Some engineering details HN might find interesting: - Zero-config auth: auto-reads Claude Code's OAT token from ~/.claude/.credentials.json, detects token type (OAT vs…

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What it does

In the maker’s words, at launch

I built an MCP server that gives Claude Code long-term memory across sessions, backed by infrastructure you control. Every Claude Code session starts from zero, no memory of previous sessions. This server uses mem0ai as a library and exposes 11 MCP tools for storing, searching, and managing memories. Qdrant handles vector storage, Ollama runs embeddings locally (bge-m3), and Neo4j optionally builds a knowledge graph. Some engineering details HN might find interesting: - Zero-config auth: auto-reads Claude Code's OAT token from ~/.claude/.credentials.json, detects token type (OAT vs API key), and configures the SDK accordingly. No separate API key needed. - Graph LLM ops (3 calls per add_memory) can be routed to Ollama (free/local), Gemini 2.5 Flash Lite (near-free), or a split-model where Gemini handles entity extraction (85.4% accuracy) and Claude handles contradiction detection (100% accuracy). Python, MIT licensed, one-command install via uvx. https://github.com/elvismdev/mem0-mcp-selfhosted

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