agentmemory vs AMA2

agentmemory and AMA2 are both agent frameworks tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

agentmemory

Orbit is an open-source agent orchestration harness that wraps coding agent runs in bounded, dependency-ordered tasks, then gates task completion on real validation: tests, lint, and type checks must pass before an orbit closes. Every run produces structured JSON artifacts — agent output, rubric scores, accept/iterate/stop recommendations, and a human-readable progress log — so you have a trail to review, not just a diff to guess at. It runs against Claude, Codex, Cursor, or any agent that speaks JSON over CLI. The demo runs without an API key, which matters when you're evaluating whether it even fits your workflow. Where it strains: teams who need a web UI, multi-agent parallelism, or cloud-managed infrastructure will hit the limits of an intentionally small CLI harness fast.

AMA2

AMA2 gives agents a native place in a shared thread — same participant model, same permissions, same persistent context — instead of bolting them on as integrations. The vendor describes a setup flow through a CLI and an MCP server connection, so agents slot into tools like Claude Code or Cursor without a separate API integration per agent. Where this hits a wall: AMA2 is infrastructure, not an agent runtime, so teams that need agents to plan and execute multi-step tasks independently still build that logic elsewhere. The shared-thread model works well when people and agents need to stay in the same conversation; it does not replace an orchestration layer for autonomous task pipelines.

Attribute	agentmemory	AMA2
Pricing	Free	Paid
Price	—	$10/mo
Free trial	No	No
Open source	Yes	No
Has API	No	Yes
Self-hosted option	Yes	No
Platforms	Linux, macOS, Windows (Python 3.6+)	—
Pros	Validation gates tied to your actual test suite and linter — not a model's self-report — which means a task cannot be marked complete when the code still breaks your build. Structured JSON artifacts on every run (agent output, rubric scores, review recommendation, progress log), so you have inspectable evidence for human review instead of reconstructing what the agent did from a diff. Agent-neutral adapter contract, so you can run the same task through Claude and Codex and compare the resulting evaluation files directly — replacing 'I think this model is better' with a logged side-by-side. Dependency-ordered backlog execution that advances one verified task at a time, which means you avoid the common failure mode where an agent skips ahead and builds on work that never actually passed. MIT licensed and self-hostable with no API key required to run the replay demo, so you can validate the harness fits your workflow before wiring it to any external service.	Agents join threads with the same participant and permission model as people, so you avoid the context reconstruction overhead that comes with every webhook-based agent call. Native persistent thread context for agents, which means agents do not lose conversation state between turns the way stateless bot integrations do. MCP server connection point means agents plug in through the tool they already use — Claude Code, Cursor, Gemini CLI — rather than requiring a separate per-agent API integration. Named role slots per agent (reply-enabled, observer) in a thread, so you get access control per participant without building a permission layer yourself. API access is available, so teams can build against AMA2 programmatically rather than being locked to the CLI-and-MCP path.
Cons	Orbit has no web UI and no managed control plane — non-engineers who need to review agent progress or trigger runs without touching a terminal cannot use it without a wrapper built on top, and building that wrapper puts the maintenance burden on your team. Task execution is sequential and single-agent per orbit: one task, one agent, one validation loop at a time. Teams that need agents running tasks in parallel — or coordinating across multiple agents on a shared codebase — hit this architectural ceiling immediately and move to a heavier orchestration framework. The adapter layer requires each coding agent to speak JSON over a CLI interface; agents without a scriptable CLI or JSON output format require a custom adapter, which the docs flag as a contribution opportunity but which in practice means engineering time before the harness is usable with those agents. There is no cloud execution or hosted option — everything runs locally or on infrastructure you manage. Teams under compliance requirements that mandate audit trails stored in a vendor-controlled environment, rather than self-managed storage, will need a different tool.	AMA2 is a messaging runtime, not an agent executor — it has no task planning or execution logic. Teams that need agents to run autonomous multi-step workflows build that logic in a separate system and use AMA2 only for the communication layer, which means two systems to maintain from the start. No self-hosted option exists. Teams operating in environments with strict data residency requirements or internal network policies cannot run AMA2 on their own infrastructure — those teams move to a self-hostable alternative rather than waiting for a deployment option the vendor has not announced. The product is in beta, and the vendor states it is free during that period — which means the pricing and feature boundaries for paid tiers, and any breaking changes to the MCP integration, are not yet fixed. Teams building production workflows on AMA2 are building on a moving target.

Bottom line

Agentmemory is free while AMA2 is paid; agentmemory is open source; only AMA2 exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between agentmemory and AMA2?

agentmemory is Free and open source, while AMA2 is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is agentmemory better than AMA2?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.