Pheebs vs MuleRun
Side-by-side comparison of features, pros & cons, pricing, and community votes (2026).
🏆 MuleRun leads with 655 upvotes
Measure how engineers and teams actually work with AI
Pheebs is an open-source telemetry tool designed to give teams insights into how they interact with AI coding agents such as Claude Code, Cursor, and Codex. Developed by Eversynced, it seamlessly integrates via hooks, unobtrusively capturing lightweight interaction signals that focus on the structure and nature of AI sessions rather than sensitive content. This makes it a valuable resource for engineering teams seeking to optimize their AI workflows, improve collaboration, and understand behavioral patterns without compromising privacy. Its open-source nature encourages customization and transparency, appealing to organizations that value control and flexibility in their data analytics. Pheebs stands out by providing a non-intrusive way to monitor AI engagement, helping teams make data-driven decisions around their AI tools and strategies.
Pros
- Open-source and highly customizable
- Lightweight integration that respects user privacy
- Focuses on session structure rather than content
- Supports popular AI coding agents like Claude Code, Cursor, and Codex
- Facilitates data-driven improvements in AI workflows
Cons
- Limited to telemetry and session shape analysis, not content
- Requires technical knowledge for setup and customization
- Currently has no built-in analytics dashboard
Best for
- • Monitoring team interactions with AI coding agents to improve workflows
- • Identifying patterns in AI usage across projects
- • Ensuring compliance and privacy by capturing only session metadata
- • Gathering data to inform training or onboarding processes
Pricing: Pricing not verified
Raise an AI that actually learns how you work
MuleRun is an innovative AI tool designed for individuals and professionals seeking a highly personalized digital assistant. Unlike traditional AI solutions, MuleRun is a self-evolving personal AI that continuously learns from your work habits, decision patterns, and preferences, becoming more refined over time. It runs seamlessly on a dedicated cloud virtual machine, operating 24/7 even when you're offline, and proactively prepares the information and resources you need before you ask. With no coding or complex setup required, users can effortlessly raise their AI and watch it adapt to their unique workflows. This makes MuleRun especially appealing to busy professionals, entrepreneurs, and teams aiming to boost productivity through tailored automation and intelligent assistance.
Pros
- Self-evolving AI that learns and improves over time
- Runs continuously on a dedicated cloud VM, ensuring 24/7 availability
- Operates offline, providing proactive support without user intervention
- No coding or technical setup needed, user-friendly onboarding
- Highly personalized, adapting to individual work habits
Cons
- Limited transparency into the AI's learning process and decision-making
- Potential privacy concerns due to continuous data collection
- Uncertain pricing structure, which may be costly for some users
Best for
- • Automating routine tasks based on learned preferences
- • Personalized productivity coaching and workflow optimization
- • Proactive content or data preparation for meetings and projects
- • Supporting e-commerce operations with tailored customer insights
Pricing: Pricing details are not explicitly provided, but likely follow a subscription-based model with tiers depending on usage and features, considering it runs on a dedicated cloud VM and offers continuous learning. A free trial or basic plan may be available, with premium plans starting around a monthly fee.