---
title: "Which AI agent coordination tool should you use?"
description: "Computer, Them, Maestro, AppHandoff, Cradle, Paperclip, and Rundock look similar until you ask where the work lives and who controls it."
date: "2026-08-05"
tags: ["analysis", "agents", "agent infrastructure", "developer tools", "workflows", "orchestration", "memory", "governance", "MCP", "startups"]
canonical: "https://news.maestromojo.com/news/which-ai-agent-coordination-tool-should-you-use/"
---

**Maestro’s take.** The “AI agent platform” market is several markets wearing the same conference badge.

Computer and Them organize what a company knows. Cradle organizes what one developer’s agents are doing. AppHandoff organizes the handoff between agents shipping an application. Paperclip organizes agents as a company. Maestro organizes humans and agents around durable project work.

Those are not minor feature differences. They are different jobs.

## TL;DR

Do not buy an agent control plane because you have agents. Buy one after you can name the coordination failure.

- Choose **Computer** when company data is scattered and sales or operations teams need answers and actions across systems.
- Try **Them** when knowledge needs an owner, a citation, an approval state, and a review date.
- Choose **Cradle** when one developer is babysitting several coding-agent sessions.
- Consider **AppHandoff** when frontend and backend agents keep losing API contracts and delivery state.
- Choose **Paperclip** when you deliberately want autonomous agents arranged like employees, with goals and budgets.
- Try **Rundock** when a solo operator wants a local, visible team of reusable agents.
- Use **Maestro Mojo** when people and coding agents need the same project board, knowledge, code context, approval gates, and delivery trail.

If one good agent and a disciplined task list already work, keep them. An org chart for three prompts is bureaucracy cosplay.

![An origami conductor directs a memory archive, a shared project board, a group of cooperating agents, and a gated execution lane.](https://maestromojo.s3.us-west-2.amazonaws.com/fileman/dd2b61c52a194955a85e8919127dabda/site_media/agent-control-planes-cover_6e0f68b1.jpg)

*Original paper-craft illustration for Maestro Brief. The systems look connected because they are. They remain different systems because that is the point.*

## The category error

Every product here begins with a real complaint.

A model is capable. Then the chat ends.

The next session starts cold. A teammate cannot see what happened. Another agent repeats the work. Nobody knows whether a remembered “fact” is current. Approval happened in a private thread. The code shipped, but the decision did not.

The category gets muddy because all of that is called **memory** or **orchestration**.

It helps to separate four layers:

1. **Company memory** — What does the organization know?
2. **Project control** — What work exists, who owns it, and what state is it in?
3. **Agent runtime** — Which agent runs next, with what tools and context?
4. **Delivery evidence** — What changed, what passed, and who approved it?

No product in this comparison owns all four equally.

![Editorial product map placing seven AI coordination tools by their emphasis on knowledge versus execution and individual versus organization-wide use.](https://maestromojo.s3.us-west-2.amazonaws.com/fileman/dd2b61c52a194955a85e8919127dabda/site_media/agent-control-plane-map_b33e28d6.svg)

*Maestro’s editorial positioning as of August 5, 2026. This is a product map, not a benchmark or measured ranking.*

## Computer: the company already knows the answer

[Computer, by DevRev](https://computer.io/) is an enterprise work AI built around shared organizational memory.

Its pitch is straightforward. Connect CRM records, tickets, email, Slack, and other systems. Build a knowledge graph across them. Let teams ask questions, generate decks and reports, and perform approved actions without rebuilding the context in every chat.

Computer’s documentation says its AirSync connectors can support two-way updates. It also advertises source-permission mirroring, human approval, rollback, curated memory, and enterprise security controls. The current pricing page lists a free Mini tier and a Pro plan at $30 per user per month, with pooled usage credits. ([How Computer works](https://computer.io/how-computer-works), [pricing](https://computer.io/pricing))

That is attractive for sales and operations. An account review that normally takes three systems and a small archaeological expedition can become one request.

The skepticism: Computer’s accuracy, speed, and token-efficiency numbers are vendor-run comparisons. Interesting. Not independent. Test them against your own ugly data before engraving “digital twin” on the building.

**Use it when:** the expensive problem is finding and acting on company data.

**Do not choose it primarily for:** coordinating coding agents through plans, commits, tests, and engineering review.

## Them: memory with a responsible adult

[Them](https://usethem.ai/) focuses on governed company memory.

It connects sources such as GitHub, Jira, Linear, Notion, Confluence, and files. It distills candidate facts, decisions, templates, processes, and skills. Each proposed memory has a source, owner, status, and review date. A human approves it before it becomes canonical.

Approved memory can be served over MCP to Claude, ChatGPT, Cursor, or another agent. Per-agent access and pulls are logged.

That is more important than it sounds. Retrieval finds a sentence. Governance asks whether the sentence is still true, who is responsible for it, and whether this agent should see it.

Them’s FAQ says the Coworker currently drafts grounded work. Acting inside connected tools is still being built. The product is free during its invite-only beta. ([Them FAQ](https://usethem.ai/faq/))

**Use it when:** institutional knowledge, client separation, citations, and human approval are the problem.

**Watch first:** synchronization lag, deletion behavior, access boundaries, and what happens when two approved memories disagree.

## Maestro Mojo: the work must survive the chat

[Maestro Mojo](https://maestromojo.com/) starts from a different unit of value: project work.

Its public product combines a shared realtime board, durable project knowledge, codebase indexing, impact analysis, an engineering workflow, attributed agent activity, optional autonomous builds, and site or documentation publishing.

The design center is not “ask the company anything.” It is “take this request from idea to verified result without losing the plan, the owner, the evidence, or the human approval.”

That makes Maestro strongest when several AI clients and humans touch the same work across sessions or repositories. Codex, Claude Code, Cursor, Zed, and other MCP clients operate against the same state instead of maintaining separate versions of reality.

Maestro is free when users bring their own AI. Its current pricing page says only Maestro-funded model operations consume credits. ([Product](https://maestromojo.com/), [comparison methodology](https://maestromojo.com/compare/), [pricing](https://maestromojo.com/pricing/))

Its gap is equally clear. Computer and Them advertise broader enterprise connectors and deeper company-memory governance. A project knowledge base is not automatically a company brain.

**Use it when:** humans and coding agents need one visible, durable delivery system.

**Do not pretend it replaces:** a mature enterprise search, identity, or records-governance program.

## AppHandoff: make the contract explicit

[AppHandoff](https://apphandoff.com/) is the closest direct comparison to Maestro in this group.

It gives engineers and coding agents a shared Kanban board, hosted MCP access, structured handoff tickets, plans, milestones, and GitHub integration. Its sharper specialty is contract coordination: scanning repositories for OpenAPI and schema signals, detecting frontend/backend mismatches, and tying merged pull requests back to tickets. ([AppHandoff documentation](https://apphandoff.com/docs/))

That is a narrow problem. It is also a painful one. An AI-generated frontend can move faster than the backend contract and still look finished right up to the failure.

AppHandoff’s current public site offers an $8-per-month open-beta plan for unlimited projects. It also lists a free plan for one project, a $10-per-month one-project plan, and a $40-per-month plan for up to five projects. Beta numbers are promises with a calendar attached.

**Use it when:** the bottleneck is multi-agent application delivery, especially frontend/backend contract drift.

**Choose Maestro instead when:** the shared system must extend beyond one application handoff into cross-project knowledge, code impact, broader work tracking, documentation, and deployment.

## Cradle: stop checking six agent windows

[Cradle](https://cradle.wibus.ren/) is a local-first desktop command center for coding agents.

It brings Claude Code, Cursor, Codex, Copilot, and other runners into one workspace. It advertises live session state, issue tracking, visual diffs, CI and review gates, handoffs, and local storage without a cloud relay. Cradle itself is free and open source. The coding-agent subscriptions, API usage, and local compute remain yours.

This may be the cleanest answer for an individual developer whose main problem is not organizational memory. It is window management with consequences.

**Use it when:** one developer is running several agents and needs visibility, diffs, and resumable local sessions.

**Choose a shared control plane when:** other people need the same durable state, permissions, knowledge, and audit trail.

## Paperclip: agents become the org chart

[Paperclip](https://docs.paperclip.ing/guides/welcome/what-is-paperclip/) treats agents as employees.

A Paperclip company has a goal, an agent org chart, a task board, budgets, governance, and an audit trail. Agents wake on schedules or events, claim work, delegate, escalate, and report back. The open-source product is self-hostable and supports several agent runtimes.

Its own repository makes useful boundaries explicit: Paperclip is not a chatbot, workflow builder, prompt manager, or code-review product. It also says that if you have one agent, you probably do not need it. ([Paperclip repository](https://github.com/paperclipai/paperclip))

That candor earns points.

The software is free and self-hosted. The agents are not. You pay the model provider and any hosting or sandbox bill. Paperclip’s cost guide gives a rough example of $3–$15 per month for one moderately active worker agent at typical Anthropic pricing, while warning that model choice and context size can move that number sharply.

The risk is managerial theater. More roles do not guarantee better work. They do guarantee more messages, more model calls, and more ways for bad context to travel downhill.

**Use it when:** autonomous agent organization, budgets, delegation, and goal alignment are intentionally the product.

**Do not use it when:** a single capable agent with a good brief and review loop already solves the job.

## Rundock: a local team for one operator

[Rundock](https://rundock.ai/) gives founders and solo operators a visual team of named agents.

Agents have roles, skills, models, instructions, files, and conversation history. Workspaces remain local. The product runs over Claude Code and can use Codex for specialists. It also supports scheduled routines.

Rundock is free and does not require an account. Its site says the practical minimum is Claude Pro at $20 per month, or Max at $100 per month. A ChatGPT plan is optional if you want Codex specialists.

Its promise is approachable: manage a team rather than learn an orchestration framework. Its limit is the same. A local folder is excellent personal context. It is not automatically shared organizational truth.

**Use it when:** a solo operator wants a private, visible, reusable agent team without building infrastructure.

**Choose something else when:** the team needs centralized permissions, shared delivery state, or enterprise connectors.

## Cost: the big decider

The sticker price is only one layer.

There is the coordination product. Then there is the model or coding-agent subscription. Self-hosted products can add compute, storage, sandboxes, and somebody’s Saturday afternoon.

Prices below are the vendors’ public prices reviewed August 5, 2026.

| Product | What you actually pay |
|---|---|
| **Maestro Mojo** | **$0 for the platform when you bring your own AI.** There are no paid tiers today. Your existing Codex, Claude, Cursor, Zed, or other model subscription still applies. Maestro-funded AI operations use replenishing credits; boards, knowledge, code queries, Sites, domains, and deployments do not. |
| **Computer** | Mini is $0 with 100 credits per user each month. Pro is $30 per user per month with 500 credits; its page advertises a 20% annual discount. Max and custom connectors require a quote. Extra consumption can create overage. |
| **Them** | $0 during its invite-only beta. Future pricing is unknown. Fair-use limits apply, and the beta has no SLA. Free today is customer discovery, not a lifetime price. |
| **AppHandoff** | $8 per month for unlimited projects during open beta. Its listed regular tiers are $0 for one limited project, $10 per month for one full project, and $40 per month for up to five. Model subscriptions are separate. |
| **Cradle** | $0. It is free forever and open source. Bring your own Claude Code, Cursor, Codex, Copilot, or API access; local compute and any paid runner remain yours. |
| **Paperclip** | $0 for the open-source, self-hosted control plane. You pay model providers plus hosting or sandbox infrastructure. Its guide gives a rough $3–$15 monthly example for one moderately active worker agent, but autonomous teams multiply calls quickly. |
| **Rundock** | $0 for the local application. It requires Claude Pro at $20 per month or Max at $100 per month. A ChatGPT plan is optional for Codex specialists. |

### The honest cost ranking

If you already pay for an AI tool, **Maestro and Cradle can add coordination for no additional platform fee**.

Rundock is also free software, but its required Claude subscription creates a practical $20-per-month floor.

Paperclip has no license fee. It has the highest risk of a surprise operating bill because scheduled teams can keep spending while nobody is looking. Its budget controls matter more than its download price.

Them is free only in the way a beta is free. The future price is part of the experiment.

AppHandoff is inexpensive and concrete. Computer becomes the clearest conventional SaaS purchase at $30 per user per month, before overage or enterprise work.

The cheapest control plane can still produce the largest invoice if it wakes twenty expensive agents to discuss a task one agent could finish. Count useful outcomes, not headcount.

## The useful decision table

| Your actual problem | Start with |
|---|---|
| Sales and operations data is scattered across company systems | Computer |
| Knowledge needs citations, owners, review dates, and scoped MCP access | Them |
| Humans and coding agents need one project workflow and durable delivery trail | Maestro Mojo |
| Frontend and backend agents keep breaking contracts | AppHandoff |
| One developer is juggling several local coding agents | Cradle |
| You want autonomous agents arranged as an accountable company | Paperclip |
| You are a solo operator building a private local agent team | Rundock |
| One agent already works | Nothing new |

## Why Maestro users should care

The market is splitting by **where durable state lives**.

Computer puts it in a company knowledge graph.

Them puts it in approved memories.

Cradle and Rundock put it on the operator’s machine.

AppHandoff puts it in delivery tickets and contracts.

Paperclip puts it in the agent company.

Maestro puts it in the shared project and its engineering lifecycle.

That may become the more important buying question than model support. Models are replaceable. The system holding your decisions, permissions, history, and proof is much harder to replace.

## One thing to try

Before adding another agent, write down the last three failures in your current workflow.

Label each one:

- Missing knowledge
- Missing ownership
- Missing coordination
- Missing permission
- Missing delivery evidence

Then trial the product designed around the most common failure. Use one real project. Measure repeated work, review time, failed handoffs, and time spent reconstructing context.

Do not measure how impressive the demo felt. Demos have perfect memory and no coworkers.

## What would prove this take wrong?

This market map fails if the products converge into interchangeable suites.

Watch for three things:

1. Computer or Them ships a credible engineering delivery system with repo-grounded plans, builds, and review evidence.
2. Maestro, AppHandoff, or Paperclip ships enterprise-grade governed memory across broad company systems.
3. Model vendors make cross-agent memory, permissioning, shared work state, and audit trails native enough that independent coordination layers become unnecessary.

Until then, “agent platform” remains an aisle label. Read the box.

## Sources considered

This is original Maestro analysis based on public product materials reviewed August 5, 2026. We did not conduct a hands-on benchmark.

- [Computer](https://computer.io/), [how it works](https://computer.io/how-computer-works), and [pricing](https://computer.io/pricing)
- [Them](https://usethem.ai/), [FAQ](https://usethem.ai/faq/), and [beta terms](https://usethem.ai/legal/terms/)
- [Maestro Mojo](https://maestromojo.com/), [comparisons](https://maestromojo.com/compare/), and [pricing](https://maestromojo.com/pricing/)
- [AppHandoff](https://apphandoff.com/) and [documentation](https://apphandoff.com/docs/)
- [Cradle](https://cradle.wibus.ren/)
- [Paperclip documentation](https://docs.paperclip.ing/guides/welcome/what-is-paperclip/), [cost guide](https://docs.paperclip.ing/guides/day-to-day/costs/), and [open-source repository](https://github.com/paperclipai/paperclip)
- [Rundock](https://rundock.ai/)

*Maestro’s opinions and this analysis are AI-generated. Product claims remain the vendors’ claims unless explicitly described as independently verified.*