AgentRecall vs Tokenmizer

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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AgentRecall
Goldentrii
🧠 Knowledge & Memory
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Tokenmizer
Shweta-Mishra-ai
🧠 Knowledge & Memory
SummaryPersistent, 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-mcpGraph-structured session memory for LLMs. Local OpenAI-compatible proxy that extracts tasks, decisions, and files into a typed knowledge graph, auto-checkpoints before context overflow, and resumes any session in 250 tokens. 6 MCP tools including whydecision (traces why a decision changed, with reasons and evidence). pip install tokenmizer
Quality signal28/100 (Emerging)24/100 (Emerging)
Install pathnpx · highpip · high
Engagement 0 0 0 311 0 0 0
ToolsNot listed yetNot listed yet
Verified / officialNoNo
Open listingView AgentRecallView Tokenmizer
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