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hippo-memory
hippo-memory logo

hippo-memory

Active·★ 784·MIT·Updated 2026-10-22
★ Trending★ Hidden Gem

Hippo is an AI agent memory layer inspired by the human hippocampus, designed to manage agent memory with features like default decay, strengthening through use, and full provenance. It integrates with various AI agents and tools, using SQLite for storage and offering a CLI for memory management, ensuring relevant context is always available without overwhelming the agent.

hippo-memory sits in the Memory & Context category, so it is usually better judged by workflow fit, deployment style, and team needs than by isolated features alone. Based on the available metadata, it leans most clearly toward Default memory decay with configurable half-life.. A representative use case is Ensuring AI agents learn from past mistakes and avoid repetition.. The listed license is MIT. GitHub stars are currently 784. Relevant tags include AI Agents, Memory Management.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool.

#AI Agents#Memory Management#Context Window#Neuroscience-inspired#SQLite#CLI Tool#Memory Decay
$ Install
$ npm install -g hippo-memory && hippo init --scan ~
↗ Visit site★ GitHub
01

Features

01Default memory decay with configurable half-life.
02Memories are strengthened through retrieval and use.
03Errors and important decisions are given longer persistence.
04Memory consolidation process ('sleep') merges and prunes memories.
05Context injection with token budgeting and flexible framing.
02

Why choose it

+Default memory decay with configurable half-life.
+Memories are strengthened through retrieval and use.
+Ensuring AI agents learn from past mistakes and avoid repetition.
+Supports 5 platforms or runtime environments.
03

Trade-offs

!The final decision should still be made through side-by-side comparison with similar tools.
04

Compatibility

Node.js
Runtime
Verified via docs
SQLite
Database
Verified via docs
AI Agent Frameworks
Integration
Verified via docs
Data Sources
Import
Verified via docs
Git
VCS
Verified via docs
05

Quick start

1
$ npm install -g hippo-memory
2
$ hippo init --scan ~
06

Use cases

↳Ensuring AI agents learn from past mistakes and avoid repetition.
↳Maintaining consistent memory across different AI agents and development tools.
↳Centralizing and making queryable memories from external systems like Slack and chat exports.
↳Providing short-term memory and task snapshots for continuous workflow.
↳Automating memory creation from git commit history and command failures.
07

Alternatives

⚡Top VS:
VSmcp-local-memory★60→VSmemora★744→VScontext-harness★42→VScaura★508→
mcp-local-memory logo
mcp-local-memory★ 60
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memora★ 744
Give your AI agents persistent memory.
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context-harness★ 42
Local-first context ingestion and retrieval for AI tools. SQLite + embeddings + MCP server for Cursor & Claude.
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caura★ 508
Caura (formerly MemClaw) — governed shared memory for AI agent fleets. Multi-agent, multi-tenant, MCP-native. Trust tiers, keystone policies, audit trails, knowledge graph, self-improving retrieval. Apache 2.0.
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montycat-mcp★ 28
Shared, persistent memory for AI agents. Self-hosted MCP server with semantic search, vector RAG, and live updates. Works with Claude, Cursor, Codex, and any MCP client.
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agents-remember logo
agents-remember★ 33
`Agents Remember` is a Drift-aware repository memory for coding agents in complex codebases. Captures what code can't say on its own! Retrieves memory by path, semantic search, and relationship (code-graph).
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memini★ 31
Give any MCP-capable agent persistent memory: remember/recall over a tiered store with hybrid vector + keyword retrieval. Single Go binary, SQLite or Postgres, embedded admin UI.
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fava-trails★ 26
🫛👣 FAVA Trails — Git-native, curated memory for AI agents via MCP. Draft isolation, promotion gate, thought lifecycle hooks, memory curation protocols, supersession chains.
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On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07Alternatives
kitfunso /
hippo-memory
↗

Biologically-inspired memory for AI agents. Decay, retrieval strengthening, consolidation. Zero runtime deps, SQLite, MCP. Benchmarked retrieval with an opt-in hosted TypeSafe Jev reranker.

784MIT
Last commit2d ago
StatusActive
CategoryMemory & Context
Links
Documentation↗Discussion↗Issues↗Releases↗
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