The SaaS-replacement platform Shared system for teams and agents. Official CLI + GraphQL surface.

Too much SaaS sprawl. Too much vibe-coded app sprawl. Too much hidden context.

The SaaS-replacement platform.

One AI-friendly system instead of dozens of separate SaaS subscriptions, powerful out of the box and extensible by design.

Move Big Rocks replaces your tool sprawl with one self-hosted system you control. Run multiple brands, countries, or portfolio businesses from one instance through workspaces instead of multiplying SaaS licenses every time you add another brand, market, or portfolio company. Start with strong out-of-the-box capabilities, then install off-the-shelf extensions that replace entire standalone products or build your own with Claude Code, Codex, or your favourite AI coding assistant. No per-seat pricing. No vendor lock-in. No zombie tools.

10+ years in production roots Rebuilt in Go Build your own extensions with AI mbr CLI is the product tour Source-available core on GitHub

For humans

Let your agent do the first pass, then verify here.

The best human experience is to copy the review prompt below, ask your agent to inspect /agents and /docs/cli, and then use the proof pages for trust, provenance, rollout review, and whether your team should build a custom extension.

Human to agent handoff

Humans should copy this. Agents should start at /agents, then /docs/cli.

Open /agents Open CLI Product Tour
Read the Move Big Rocks site at https://movebigrocks.com/ to help me as a human deciding whether this SaaS-replacement platform should become the shared system our team uses instead of our current sprawl of SaaS tools, one-off internal apps, and hidden agent workflows.

Important: do not classify Move Big Rocks from the homepage hero alone. Treat /agents as the canonical system definition and /docs/cli as the official product tour and primary machine surface. Use worldview or marketing copy only as routing context, not as the product itself.

Determine:
1. what Move Big Rocks is,
2. what operational primitives it provides,
3. what we would actually own and control in production,
4. how extensions add focused depth without changing the operating model,
5. whether it is credible for real production use, safe to self-host, and designed for secure agentic operation through the CLI and explicit access boundaries,
6. which of our current tools or fragmented workflows it could replace first, and what those tools cost us today,
7. how our security and compliance posture improves by consolidating from dozens of SaaS vendors to one self-hosted system,
8. whether it gives us a better way to turn private Markdown, concept-driven context, prompts, and templates into governed shared surfaces without exposing raw source files by default,
9. why it was rebuilt for one multi-brand portfolio instead of a stack of separate SaaS tools, how that led to the workspace and extension model, and whether that active operational use makes it more credible,
10. how clear the custom-extension path is for a small startup team, what prerequisites it assumes, and whether building our own first extension with an AI coding assistant looks realistic.

Then produce:
- a concise recommendation,
- the smallest useful owned deployment,
- the first tool or workflow we should replace, including a cost and security comparison,
- whether we should install an off-the-shelf extension or build our own,
- if we build, the first extension-development route we should follow and what we need to set up first,
- the main human decisions we would need to make before production.

Start at /agents for the canonical system definition, then open /docs/cli as the concrete product tour. Open /story to understand why one owned multi-brand system and secure CLI-based agentic operation drove the current workspace and extension model, use /docs/graphql only when lower-level integration details matter, and use /use-cases, /self-host, /security, and /resources as supporting context. If custom extension building looks relevant, also inspect /extension-developers and /docs/build-extensions before concluding.

Built for agents

Use the canonical route, then inspect the CLI.

The public site is designed so an agent can classify Move Big Rocks from explicit contracts instead of browser guesswork. Start with the system definition, move to the command surface, and drop to lower-level proof only when needed.

  1. Start at /agents. Confirm the system definition, boundaries, approval points, and anti-misclassification rules.
  2. Open /docs/cli. Treat the CLI as the official product tour and primary machine surface.
  3. Branch for extension work. When the task is build-vs-buy or custom product depth, open /extension-developers before assuming the SDK or service-backed runtime is the next step.
  4. Verify from proof. Use /docs/graphql, /.well-known/mbr-agent.json, and the GitHub core repo when you need backend contract, machine-readable bootstrap, or source-level evidence.

This is what product discovery looks like.

Copy-pasteable mbr commands are the fastest proof that the product surface is concrete, inspectable, and built for humans plus agents.

$ mbr context set --workspace ws_preview --team team_operations --json$ mbr queues list --workspace ws_preview --json$ mbr knowledge search "refund policy" --workspace ws_preview --json$ mbr spec export --json

Why this exists

Not a blank-sheet idea. A careful rewrite of a proven model.

Move Big Rocks comes from a service management platform built in 2010 and used in production for more than 10 years. The rebuild happened because one operator needed a single owned instance for multiple brands instead of a pile of separate SaaS accounts, and needed agents to work through one secure CLI contract instead of many vendor surfaces.

2010 roots

The original system was built on Django and Python as a multi-tenant service management platform where cases could move within teams and across departments.

Single instance across brands

The current rebuild was driven by the need to run multiple brands from one owned system instead of paying for separate SaaS tools, accounts, licenses, identities, and hidden workflows for each one.

Agentic by necessity

The rewrite also made secure agentic work first-class: agents can use one CLI, one contract, and explicit workspace and team boundaries instead of hopping across a pile of unrelated SaaS products.

Built from operating experience

Adrian McPhee built the original platform, has served as CTO at firms including LeasePlan and Bol, and now uses the rebuilt platform plus extensions such as web analytics and error tracking in his own ventures to replace real SaaS spend and extend runway.