AgentIndex icon
AgentIndex
anneal-memory logo
anneal-memory
★ 12
vs
engrim logo
engrim
★ 299

anneal-memory vs engrim

anneal-memory: anneal-memory provides living, auditable, and quality-controlled memory for AI agents, featuring structural defenses against sycophancy and junk accumulation. It implements a complementary learning systems architecture with episodic, continuity, crystallized, and prospective memory layers, all built with zero external dependencies.; 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.

01

TL;DR

anneal-memory logo
anneal-memoryMemory & Context · ★ 12

Integrating robust, auditable memory into custom AI agent frameworks.

Read anneal-memory full review →
engrim logo
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 →
02

Side-by-Side Comparison

Field
anneal-memory logoanneal-memory
engrim logoengrim
Category
Memory & Context
Memory & Context
Stars
★ 12
★ 299
License
MIT
MIT
Install Command
pip install anneal-memory
pip install engrim
Updated
5d ago
3w ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
AI Agent Memory, Memory Management, Cognitive Architecture
Episodic Memory, LLM Context Management, AI Agents
03

Features

anneal-memory logoanneal-memory
01Citation-Validated Memory Graduation
02Tamper-Evident Audit Trail
03Sycophancy and Junk Accumulation Prevention
04Complementary Learning Systems Architecture
05Zero-Dependency Python Library
engrim logoengrim
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.
04

Use Cases

anneal-memory logoanneal-memory
↳Integrating robust, auditable memory into custom AI agent frameworks.
↳Developing AI systems that require high integrity and verifiable decision-making.
↳Building multi-session AI agents that resist memory drift, sycophancy, and junk accumulation.
↳Implementing long-term knowledge management for LLM-powered applications, separating active context from crystallized wisdom.
↳Compliance and auditing for AI systems, providing traceability for AI actions and decisions.
engrim logoengrim
↳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.
FAQ

FAQ

What is the difference between anneal-memory and engrim?
Both anneal-memory and engrim are in the Memory & Context category. anneal-memory has 12 stars, while engrim has 299 stars.
Which is better, anneal-memory or engrim?
The best choice depends on your use case. Choose anneal-memory if Integrating robust, auditable memory into custom AI agent frameworks., 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 anneal-memory free or open source?
Yes, anneal-memory is open source on GitHub (MIT).
Is engrim free or open source?
Yes, engrim is open source on GitHub (MIT).
Cloud Infrastructure
Ad

Deploy on DigitalOcean

Host your MCP servers, Docker containers, and AI agents with $200 free credit over 60 days.

Claim $200 Free Credit
→

Related

Alternatives to anneal-memory →Alternatives to engrim →anneal-memory details →engrim details →