memini
★ 28
vs
okf-agent-memory
★ 827
memini vs okf-agent-memory
memini: memini is a shared, persistent memory service designed for AI agents, providing a single location for agents to remember and recall information with continuously improving retrieval quality. It's built as a Go binary, offers zero-configuration startup, and scales from embedded SQLite on a laptop to Postgres in Kubernetes.; okf-agent-memory: OKF Agent Memory provides a domain-neutral, Git-native persistent project memory for AI agents, leveraging the Dual-Memory Agent Architecture to prevent context bloat and memory rot. It uses an ultra-compact behavioral codex and a queryable OKF v0.2 knowledge bundle, with blazing-fast, zero-cost local retrieval.
01
TL;DR
meminiMemory & Context · ★ 28
Enhancing AI Agents with Long-Term Memory: Integrate memini to give AI agents (like Claude Code, opencode, Hermes) the ability to remember past interactions and learn over time.
okf-agent-memoryMemory & Context · ★ 827
Software Engineering: Managing architecture decisions, code references, and operational constraints.
02
Side-by-Side Comparison
Field
meminiokf-agent-memoryCategory
Memory & Context
Memory & Context
Stars
★ 28
★ 827
License
AGPL-3.0
MIT
Install Command
export MEMINI_EMBED_BASE_URL=http://localhost:8081/v1 && export MEMINI_EMBED_MODEL=bge-m3 && export MEMINI_EMBED_DIMS=1024 && mise run run
git clone https://github.com/okf-memory/okf-agent-memory.git && cd okf-agent-memory && make build
Updated
3d ago
1d ago
Open Source
Yes
Yes
Tags
AI Agents, Persistent Memory, Vector Search
AI Agents, Persistent Memory, Knowledge Base
03
Features
memini01Shared, Persistent Memory: Provides a dedicated service for AI agents to store and retrieve memories, designed for long-term persistence.
02Hybrid Retrieval & Re-ranking: Employs a hybrid (vector + keyword) retrieval method, fused with Reciprocal Rank Fusion (RRF), and re-ranks results by relevance, recency, and importance, not just similarity.
03Tiered Memory System: Implements a tiered memory structure (working, episodic, semantic, procedural) with decay mechanisms.
04Pluggable Storage: Supports flexible storage options, including embedded SQLite-vec for local use and Postgres with VectorChord for scalable deployments.
05Optional LLM Consolidation: Features an opt-in LLM consolidation pipeline for background deduplication and contradiction resolution, but can run headless (without an LLM) using marker heuristics.
06Model Context Protocol (MCP) Support: Compatible with MCP-capable agents, offering both Streamable HTTP and stdio transports.
okf-agent-memory01Dual-Memory Cognitive Architecture (DMAA) to eliminate prompt bloat.
02Blazing fast performance with in-memory BM25 search (<300µs) and graph validation (~4ms).
03100% Git-native, zero vendor lock-in, and zero API costs for memory retrieval.
04Built on Google's Open Knowledge Format (OKF) v0.2 for standardized agent knowledge.
05Solves context bloat and memory rot through progressive disclosure and Search-Before-Write principle.
04
Use Cases
memini↳Enhancing AI Agents with Long-Term Memory: Integrate memini to give AI agents (like Claude Code, opencode, Hermes) the ability to remember past interactions and learn over time.
↳Self-Hosting a Shared Memory Service: Deploy memini for a team or homelab environment to provide a centralized, persistent memory store for multiple AI agents.
↳Improving AI Recall Quality: Tune memini's retrieval parameters to fix bad recall and achieve higher accuracy in retrieving relevant information for AI models.
↳Managing Multi-Agent Namespaces: Lay out distinct namespaces within memini to provide isolation and organized memory management for several different AI agents.
↳Backend for Open WebUI Memory: Utilize memini as a robust memory backend for platforms like Open WebUI, integrating its memory and tool capabilities.
okf-agent-memory↳Software Engineering: Managing architecture decisions, code references, and operational constraints.
↳Scientific Research & Literature Reviews: Organizing and querying research findings and insights.
↳Coaching & Operations: Storing client session history, ethical guidelines, and runbooks.
↳Multi-Agent Collaboration: Providing a shared, auditable knowledge base for autonomous agents.
05
Best For
memini—
okf-agent-memoryHidden Gem
FAQ
FAQ
What is the difference between memini and okf-agent-memory?
Both memini and okf-agent-memory are in the Memory & Context category. memini has 28 stars, while okf-agent-memory has 827 stars.
Which is better, memini or okf-agent-memory?
The best choice depends on your use case. Choose memini if Enhancing AI Agents with Long-Term Memory: Integrate memini to give AI agents (like Claude Code, opencode, Hermes) the ability to remember past interactions and learn over time., and okf-agent-memory if Software Engineering: Managing architecture decisions, code references, and operational constraints..
Is memini free or open source?
Yes, memini is open source on GitHub (AGPL-3.0).
Is okf-agent-memory free or open source?
Yes, okf-agent-memory is open source on GitHub (MIT).
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