AgentMemory vs gpt-engineer

AgentMemory

Agents

gpt-engineer

Agents

Tagline

AgentMemory

Open-source persistent memory runtime for AI coding agents, with hybrid retrieval and zero external dependencies.

gpt-engineer

Describe software in natural language, watch an AI agent write, run, and improve it.

Pricing

AgentMemory

Free· Free, open-source (Apache 2.0); bring your own LLM API key

gpt-engineer

Free· Free and open source under MIT license. Users pay only for the underlying LLM API calls (OpenAI, Anthropic, Azure OpenAI) or run local models at zero token cost.

API

AgentMemory

Yes

gpt-engineer

Not listed

Platforms

AgentMemory

cliapi

gpt-engineer

—

Open source

AgentMemory

Yes · Apache-2.0

gpt-engineer

Yes · MIT

GitHub stars

AgentMemory

29,984

checked 2026-10-29

gpt-engineer

54,998

checked 2026-10-29

Last GitHub push

AgentMemory

2026-10-28

gpt-engineer

2025-05-14

First commit

AgentMemory

2026-02

gpt-engineer

2023-04

Package downloads (30 d)

AgentMemory

77,138 · npm @agentmemory/agentmemory

checked 2026-11-07

gpt-engineer

795 · pypi gpt-engineer

checked 2026-10-12

Hacker News stories

AgentMemory

1

checked 2026-11-07

gpt-engineer

—

Earliest Wayback capture

AgentMemory

2026-04-19

earliest archived capture of the site, not a launch date

gpt-engineer

—

Company

AgentMemory

AgentMemory

gpt-engineer

—

Model used

AgentMemory

Multi-model (Claude, Gemini, MiniMax, OpenRouter)

gpt-engineer

OpenAI GPT (default), Anthropic Claude, Azure OpenAI, and open-weights models like WizardCoder via configuration

Best for

AgentMemory

Pick AgentMemory if you want a drop-in, self-hosted memory layer for your coding agent stack without running a vector DB or graph store.

gpt-engineer

Developers, researchers, and tinkerers who want a hackable, model-agnostic CLI coding agent they can script, fork, or benchmark without paying for a platform.

Not for

AgentMemory

Skip it if you need a hosted, multi-tenant memory service with SLAs or a production-grade datastore behind it.

gpt-engineer

Teams needing an actively maintained, IDE-integrated agent for large production codebases — pick Aider, Cursor, Claude Code, or Cline instead.

Editorial score

AgentMemory

7.3 / 10

gpt-engineer

—

Use cases

AgentMemory

agent-memorycoding-agentscontext-managementknowledge-graphmcp-server

gpt-engineer

Greenfield script and prototype generationSmall single-file utility creation from a specIterative code improvement via improve modeCoding-agent research and benchmarking (APPS, MBPP)Teaching example for LLM agent loopsScriptable code generation in CI pipelinesLocal-model code generation with self-hosted LLMs

Pros

AgentMemory

• Zero external infrastructure: single Node process, JSON on disk
• Triple-stream retrieval (BM25 + vectors + graph) with sub-20ms recall
• Native plugins for Claude Code, Cursor, Cline, Windsurf, and 15+ agents
• Apache 2.0, runs on your existing LLM subscription
• Strong benchmark numbers (95.2% R@5 on LongMemEval-S)

gpt-engineer

• Fully open source (MIT) with a small, readable codebase that's easy to fork or study.
• Model-agnostic: swap OpenAI, Azure OpenAI, Anthropic, or local open-weights models.
• Zero platform cost — you pay only for tokens, or nothing at all with local models.
• Simple CLI-first workflow (`gpte <dir>`) that scripts and CI can call.
• Built-in improve mode for iterating on existing code, not just greenfield generation.
• Preprompt customization lets you retune agent behavior without patching source.
• Ships with benchmarking against APPS and MBPP for coding-agent research.

Cons

AgentMemory

• Pre-1.0 (v0.9.27), expect breaking changes
• Single-process JSON storage may not scale to team-wide deployments
• Self-hosted only; you operate the runtime
• Effectiveness depends on the LLM provider you wire in

gpt-engineer

• Repository was archived in April 2026 — no active maintenance, bug fixes, or new model support.
• Best suited to small greenfield projects; struggles on large multi-file codebases.
• No IDE integration — lives entirely in a terminal with a text prompt file.
• Requires bring-your-own API keys and manual configuration for non-OpenAI models.
• Python 3.10-3.12 only; older environments are unsupported.
• Newer agents (Aider, Cursor, Claude Code, Cline) have overtaken it on both quality and DX.

Website

AgentMemory

agent-memory.dev

gpt-engineer

github.com

Editorial score: rule-based, 0–10, from AI-assisted profile inputs (see /methodology) — not a user rating; “—” means unscored. “Not listed” means we have no record of it, not that it is absent. GitHub figures and prices carry the date they were checked or captured; prices are shown as published, unconverted.