ModuleX vs Worktrunk: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of ModuleX and Worktrunk — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

ModuleX

Freemium

An AI workflow orchestration platform to build with natural language or a visual canvas, connect 600+ tools, and run any major AI model.

Natural-Language & Visual Builder: Build workflows by describing them in plain language or using a visual canvas.
600+ Tool Integrations: Connect CRMs, databases, communication tools, and more across your stack.
Any Major AI Model: Run workflows with every major AI model using your own keys at provider rates.
Deep Agentic Assistant: Describe a goal and a deep agent reasons, picks the right tools, and executes across integrations.
Multiple Execution Modes: Trigger workflows via chat, SDK, or REST API.
Real-Time Cost Visibility: See every step and its cost in real time as workflows run.
Developer SDKs: Native JavaScript and Python SDKs plus curl/REST endpoints for embedding automation.

Business Automation: Orchestrate multi-step workflows across CRM, database, and communication tools.
Agentic Task Execution: Hand a goal to the deep agent and let it select tools and complete it.
Developer Integration: Trigger workflows programmatically from code via SDK or REST API.
Cost-Controlled AI: Use your own API keys to keep model costs transparent and predictable.

max-sixty

Free

A Rust CLI that makes git worktrees as easy as branches, built for running several AI coding agents in parallel without collisions.

Branch-Addressed Worktrees: wt switch, wt remove, and wt list refer to worktrees by branch name with paths computed from a configurable template, replacing multi-step git worktree incantations.
Agent Launch in One Command: wt switch -c -x claude <branch> creates the worktree, enters it, and starts the agent in a single invocation.
Lifecycle Hooks: Run commands automatically on create, pre-merge, and post-merge to automate setup and teardown for every new worktree.
LLM Commit Messages: Generates commit messages from the diff so parallel agent branches stay legible without hand-writing every message.
One-Command Merge Workflow: Squash, rebase, merge, and clean up the worktree and branch in a single step rather than a sequence of git commands.
Interactive Picker: Browse worktrees with streaming CI status alongside diff, log, PR, and comment previews before switching.
Shared Build Caches: wt step copy-ignored gives ten worktrees their own target/ and node_modules/ without rebuilding or copying, using reflinks on APFS, btrfs, and XFS.
Per-Worktree Dev Servers: A hash-port template filter assigns each worktree a unique port so parallel dev servers do not conflict.

Parallel Agent Runs: Give each of five to ten concurrently running AI coding agents its own worktree so their edits never collide.
Fast Branch Context Switching: Jump between in-flight changes by branch name instead of navigating sibling directories by path.
Pull Request Review: wt switch pr:123 checks out a pull request's branch directly for local inspection or testing.
Monorepo Iteration: Share heavy build artifacts across many worktrees so each new branch is usable immediately instead of after a full rebuild.
Automated Branch Setup: Use create hooks to install dependencies, copy env files, or start services whenever a worktree is made.
Multi-Branch Status Review: wt list --full shows CI status and AI-generated summaries for every active branch in one view.