okf-agent-memory

★ 830

engrim

★ 299

okf-agent-memory vs engrim

Q: What is the difference between okf-agent-memory and engrim?

Both okf-agent-memory and engrim are in the Memory & Context category. okf-agent-memory has 830 stars, while engrim has 299 stars.

Q: Which is better, okf-agent-memory or engrim?

By GitHub stars, okf-agent-memory has more community adoption, but the best choice depends on your specific use case.

Q: Is okf-agent-memory free or open source?

Yes, okf-agent-memory is open source on GitHub (MIT).

Q: Is engrim free or open source?

Yes, engrim is open source on GitHub (MIT).

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.; engrim: Engrim is a universal, local-first SQLite memory engine specifically engineered for autonomous AI coding agents, designed to solve the '200,000-token context window trap'. It provides high-precision, curated episodic working memory, allowing developers to switch between various models and environments on the same codebase without losing architectural decisions or project state.

TL;DR

okf-agent-memoryMemory & Context · ★ 830

Software Engineering: Managing architecture decisions, code references, and operational constraints.

Read okf-agent-memory full review →

engrimMemory & Context · ★ 299

Maintaining Project Context Across Agent Sessions: Developers can use Engrim to prevent LLMs from losing architectural decisions, user constraints, or project state when chat sessions are cleared or models are switched.

Read engrim full review →

Side-by-Side Comparison

Field

okf-agent-memory

engrim

Features

okf-agent-memory

01Dual-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.

engrim

01Precision Working Memory: Replaces raw transcript replay with ~4,000 characters of high-precision, curated episodic memory, injected at boot with zero attention dilution.

02Cross-Model/Agent Compatibility: Provides a universal substrate for memory, allowing decisions made in one agent (e.g., Claude Code) to be visible and usable in others (e.g., Antigravity, Cursor).

03Local-First & Private Storage: Stores all memories locally in a SQLite file (~/.engrim/memory.db) with WAL mode and POSIX 0600 permissions, ensuring 100% privacy with no cloud sync or telemetry.

04Self-Healing Diagnostics: The `engrim doctor --fix` command verifies all hooks and installs portable PATH fallbacks, ensuring reliable operation across machines and OSes without silent failures.

05Hybrid Retrieval & Minder: Employs a hybrid lexical (BM25) and vector (model2vec) search for efficient and relevant memory recall in approximately 30ms.

Use Cases

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.

engrim

↳Maintaining Project Context Across Agent Sessions: Developers can use Engrim to prevent LLMs from losing architectural decisions, user constraints, or project state when chat sessions are cleared or models are switched.

↳Collaborative Multi-Agent Development: Enabling multiple AI coding agents (e.g., Antigravity, Claude Code, Cursor) to work on the same codebase and share a consistent, evolving memory store.

↳Continue-As-Clear Workflow: Allows users to clear their agent's context window at any time, with Engrim automatically re-injecting the active memory pack for seamless continuation without memory loss.

↳Auditing Agent Provenance: Tracking which agent made specific architectural decisions or added facts to the project's memory, enhancing transparency in multi-agent environments.

Best For

okf-agent-memory

Hidden Gem

engrim

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FAQ

What is the difference between okf-agent-memory and engrim?

Both okf-agent-memory and engrim are in the Memory & Context category. okf-agent-memory has 830 stars, while engrim has 299 stars.

Which is better, okf-agent-memory or engrim?

The best choice depends on your use case. Choose okf-agent-memory if Software Engineering: Managing architecture decisions, code references, and operational constraints., and engrim if Maintaining Project Context Across Agent Sessions: Developers can use Engrim to prevent LLMs from losing architectural decisions, user constraints, or project state when chat sessions are cleared or models are switched..

Is okf-agent-memory free or open source?

Yes, okf-agent-memory is open source on GitHub (MIT).

Is engrim free or open source?

Yes, engrim is open source on GitHub (MIT).

Cloud Infrastructure

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Alternatives to okf-agent-memory →Alternatives to engrim →okf-agent-memory details →engrim details →

TL;DR

Side-by-Side Comparison

Features

Use Cases

Best For

FAQ

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