Mnemostack vs AgentRecall

Side-by-side comparison of two Model Context Protocol servers — install paths, tools, quality signals, and directory engagement so you can pick the right one for Claude, Cursor, and other MCP clients.

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Mnemostack
udjin-labs
🧠 Knowledge & Memory
A
AgentRecall
Goldentrii
🧠 Knowledge & Memory
SummaryDurable hybrid memory for AI agents. Combines vector search, BM25, temporal retrieval, and optional Memgraph knowledge graph via reciprocal rank fusion. 6 MCP tools: health, search, answer, feedback, graphquery, graphaddtriple. Self-hosted with Qdrant backend. 82.5% strict accuracy on LoCoMo benchmark. pip install 'mnemostack[mcp]'Persistent, compounding memory for AI agents across sessions. Uses the Intelligent Distance Protocol to surface the most contextually relevant past memories. Five tools: sessionstart, remember, recall, check, sessionend. npx agent-recall-mcp
Quality signal23/100 (Emerging)28/100 (Emerging)
Install pathnpx · lownpx · high
Engagement 0 0 0 0 0 0 311
ToolsNot listed yetNot listed yet
Verified / officialNoNo
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