vstorm-co/memv
Structured, temporal memory for AI agents.
This project helps AI developers build more intelligent and context-aware AI agents by providing a sophisticated memory system. It takes in conversational exchanges (user messages and agent responses) and intelligently extracts only the most relevant, new information, allowing the agent to remember facts, track changes over time, and recall specific details. AI engineers and developers creating conversational AI, virtual assistants, or autonomous agents would find this useful.
Use this if you are building an AI agent and need it to remember specific details from past conversations, understand how information changes over time, and recall context for more natural and informed interactions.
Not ideal if you simply need to store unstructured text or a basic log of interactions without needing advanced temporal tracking, contradiction handling, or intelligent fact extraction for an AI agent.
Stars
51
Forks
4
Language
Python
License
MIT
Category
Last pushed
Mar 12, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/agents/vstorm-co/memv"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Featured in
Higher-rated alternatives
kayba-ai/agentic-context-engine
🧠 Make your agents learn from experience. Now available as a hosted solution at kayba.ai
MemMachine/MemMachine
Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory...
knowns-dev/knowns
The memory layer for AI-native development — giving AI persistent understanding of your software...
rexdivakar/HippocampAI
HippocampAI — Autonomous Memory Engine for LLM Agents
Dicklesworthstone/cass_memory_system
Procedural memory for AI coding agents: transforms scattered session history into persistent,...