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sachitrafa/YourMemory

by Various

Agentic AI memory with Ebbinghaus forgetting curve decay. +16pp better recall than Mem0 on LoCoMo.

S

MCP

sachitrafa/YourMemory

Added 1 June 2026

#ai-agents #claude #ebbinghaus #llm-memory #mcp #memory #model-context-protocol #pgvector

Overview

YourMemory is a Python library that implements agentic AI memory using Ebbinghaus forgetting curve decay to model how memories fade over time. It reports a 16 percentage point improvement in recall over Mem0 on the LoCoMo benchmark.

Best for

Best for
Developers building AI agents with persistent, time-decaying memory

Use cases

  • Implementing long-term memory for AI agents
  • Improving recall in conversational AI systems
  • Creating context-aware agents with time-decaying memory

Notes

YourMemory is a Python library that implements agentic AI memory using Ebbinghaus forgetting curve decay to model how memories fade over time. It reports a 16 percentage point improvement in recall over Mem0 on the LoCoMo benchmark.

232 stars on GitHub. Last updated 2026-05-30.

Use cases

  • Implementing long-term memory for AI agents
  • Improving recall in conversational AI systems
  • Creating context-aware agents with time-decaying memory

Pros

  • Achieves +16pp recall over Mem0 on LoCoMo
  • Uses Ebbinghaus forgetting curve for realistic memory decay
  • Open-source Python library with 232 GitHub stars

Cons

  • Benchmark limited to LoCoMo dataset
  • Requires additional integration work for production systems
  • Small community compared to Mem0

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Achieves +16pp recall over Mem0 on LoCoMo
  • Uses Ebbinghaus forgetting curve for realistic memory decay
  • Open-source Python library with 232 GitHub stars

Cons

  • Benchmark limited to LoCoMo dataset
  • Requires additional integration work for production systems
  • Small community compared to Mem0

Pairs with

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