MakersClaw vs tutti

MakersClaw and tutti are both ai agent apps 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.

MakersClaw

MakersClaw provides dedicated, always-on AI agents targeted at customer support via messaging apps, sales outreach, and research tasks running in isolated containers. Each agent instance is persistent rather than session-bound, which means a support queue that arrives at midnight does not wait until morning. The platform pairs agent management with a built-in CRM and a playground environment for testing workflows before they go live. The scrape surface is thin — the vendor's public page exposes navigation labels but limited technical depth — so specifics around API rate limits, supported messaging integrations, and container isolation guarantees are not independently verifiable from available documentation. Teams evaluating this for production workloads will need to pressure-test those boundaries before committing.

tutti

The core idea: instead of agents exchanging summaries, they share a live project state. Codex sees exactly what Claude changed, what's running, and what's pending — no copy-paste required. The `@` reference system lets any agent or teammate pull from any file or conversation in the workspace without re-uploading. A GUI control center surfaces every pending approval and running task in one view, so you sign off without opening a terminal. The ceiling appears when your workflow involves agents outside Tutti's supported roster or when you need fine-grained infra control — the platform is built for GUI-driven coordination, not headless pipeline automation.

Attribute	MakersClaw	tutti
Pricing	Paid	Free
Price	$49/mo	—
Free trial	No	No
Open source	No	Yes
Has API	No	No
Self-hosted option	No	No
Platforms	Web	—
Pros	Persistent 24/7 agent instances, so a customer support queue or sales sequence keeps running through off-hours without a human restarting sessions or monitoring a process. Built-in CRM paired directly with agent activity, which means interaction history lands in contact records automatically rather than requiring a separate integration or manual export step. Playground environment for testing agent behavior before live deployment, so you catch broken prompts or misrouted logic in staging rather than in front of a customer. Research tasks described as running in secure containers, which provides a degree of execution isolation for agents handling sensitive or multi-step retrieval work. Freemium entry with a free credit allocation, so teams can validate whether the agent behavior matches their use case before any budget commitment.	Shared live project state across agents, so Codex reads exactly what Claude produced without a re-briefing step — eliminating the context decay that compounds across every handoff. The `@` reference system lets any agent pull any file or conversation from the workspace by name, so the copy-paste loop between agent sessions stops entirely. Goal-to-task decomposition with manual assignment review, so you keep control over which agent runs each step without scripting the breakdown yourself. Apps run inside the workspace and are callable by agents using existing subscriptions, so Claude can write a PRD and directly invoke a design tool without switching windows or re-authenticating. GUI control center aggregates every running task and pending approval in one view with one-click sign-off, so you stay in the loop without monitoring separate agent sessions across multiple tabs.
Cons	No self-hosted or local-run option exists, which means teams with strict data residency requirements or air-gapped environments cannot use this product at all — that is the condition under which a team moves to an open-source alternative like n8n or a self-hosted LangChain setup. Public technical documentation is sparse based on available page content, so details like API rate limits, supported messaging platform connectors, and container isolation specifications require direct vendor contact to verify — a team building a production integration cannot pre-validate those constraints from public sources alone. The platform is hosted-only and managed by a single vendor (MakersClaw), meaning an outage or pricing change sits entirely outside your control; teams running revenue-critical agents need a contingency plan that the architecture does not currently provide.	Teams that need headless, programmatic pipeline control — triggering agents via API, chaining steps based on returned values, running without a GUI — hit a structural wall. Tutti is built around a visual workspace; there is no evident scripted orchestration layer for fully automated pipelines. Those teams move to a code-first framework or an API-driven orchestration tool instead. The in-workspace app catalog is community-and-vendor-built and early-stage. When a workflow requires an app or integration that does not exist in the catalog, teams either build a custom app (which requires development time Tutti does not eliminate) or accept that the agent must leave the workspace to use an external tool, breaking the shared-state model. Agent support is bounded by whichever models Tutti explicitly connects — Claude, Codex are named in the vendor content. Teams running workflows on models or providers outside that set cannot bring those agents into the shared workspace, which forces the same copy-paste context problem Tutti exists to solve.

Bottom line

MakersClaw is paid while tutti is free; tutti is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between MakersClaw and tutti?

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

Is MakersClaw better than tutti?

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.