Cloudways Managed AI Agents
Cloudways AI Agent Hosting: OpenClaw, Hermes, Pricing & Sizing
Cloudways AI Agent Hosting is a managed way to run persistent AI agents such as OpenClaw and Hermes without building and maintaining the underlying server yourself. You still choose the agent, connect your own model provider, decide where the instance should run, and configure the workflows, but Cloudways takes responsibility for the infrastructure layer, deployment process, security patching and routine server operations that would otherwise sit on your own VPS checklist.
The real buying decision is not simply whether managed hosting sounds convenient. You need to know which agent fits the way you work, which instance has enough CPU and memory, how model-provider charges affect the true monthly cost, and whether messaging channels, scheduled jobs, sub-agents or MCP connections will push the workload beyond an entry plan. The calculator below turns those decisions into a practical starting recommendation.
Interactive tool
Cloudways AI Agent Hosting Size Calculator
Estimate the smallest sensible Cloudways instance from workload, concurrency, channels, sub-agents and runtime pattern. The result is a planning recommendation, not a benchmark guarantee.
Quick answer
Is Cloudways Managed AI Agent Hosting worth using for OpenClaw or Hermes?
Cloudways is most compelling when you want a persistent OpenClaw or Hermes deployment but do not want to spend time provisioning a server, hardening it, keeping the runtime patched, managing backups and diagnosing infrastructure problems before you can use the agent. The service does not replace your LLM provider. You bring your own OpenAI, Anthropic, Google or other supported key, and those model charges remain separate from the Cloudways server bill.
For light personal automation, Scout is the natural starting tier. Operator fits an agent that is active every day, Squad adds headroom for multiple workflows or sub-agents, and Swarm is the high-end option for many tools or agents running continuously. Cloudways currently advertises a separate Managed AI Agents promotion, so compare the live checkout price with the standard plan prices shown in this guide.
Cloudways AI Agent Hosting plans at a glance
These are the standard instance resources Cloudways currently publishes for Managed AI Agents. The calculator uses them as the baseline rather than inventing a separate sizing scale.
| Plan | Compute | Storage / bandwidth | Standard price | Best starting fit |
|---|---|---|---|---|
| Scout | 1 vCPU / 2 GB RAM | 50 GB SSD / 2 TB bandwidth | $9.99/mo standard | Light checks, testing and one or two simple workflows |
| Operator | 2 vCPU / 4 GB RAM | 80 GB SSD / 3 TB bandwidth | $19.99/mo standard | An active agent doing focused, regular work |
| Squad | 4 vCPU / 8 GB RAM | 160 GB SSD / 5 TB bandwidth | $39.99/mo standard | Multiple workflows or coordinated sub-agents |
| Swarm | 8 vCPU / 16 GB RAM | 320 GB SSD / 6 TB bandwidth | $79.99/mo standard | Many tools, agents and continuous production activity |
Current standard pricing
Cloudways Managed AI Agent instance plans
LLM provider usage is billed separately.
- 1 vCPU
- 2 GB RAM
- 50 GB SSD
- 2 TB bandwidth
- 2 vCPU
- 4 GB RAM
- 80 GB SSD
- 3 TB bandwidth
- 4 vCPU
- 8 GB RAM
- 160 GB SSD
- 5 TB bandwidth
- 8 vCPU
- 16 GB RAM
- 320 GB SSD
- 6 TB bandwidth
What Cloudways manages and what you still control
With a self-managed VPS, the agent is only one part of the job. You also own the operating system, runtime dependencies, exposed services, firewall choices, updates, backups, process restarts and the small configuration problems that appear after an upstream release. Cloudways moves that infrastructure work into a managed product. The point is not that technical knowledge becomes unnecessary, but that routine server administration no longer has to be the first task every time you want to experiment with an agent.
You still control the behavior that matters most. That includes the agent you deploy, the model provider and API key, the channels you connect, the skills or tools you enable, any MCP servers you attach and the prompts or policies that govern automation. Those choices determine what the agent can see and do. Managed hosting should therefore be treated as an operational foundation, not as a permission system that automatically makes every workflow safe.
This division of responsibility is useful for agencies, founders and technical teams because it separates infrastructure reliability from agent design. A developer can focus on workflows while another person controls model budgets and access. If an agent is used for production tasks, you should still document who owns credentials, which external systems are connected, what actions require approval and how the agent is recovered if a configuration or integration fails.
OpenClaw and Hermes are not the same product
OpenClaw is the more natural choice when you picture the agent as a broad assistant that stays reachable through the communication tools you already use. Cloudways describes OpenClaw as working with messaging channels such as WhatsApp, Slack, Discord and Telegram, while also supporting terminal access and connections to tools. Its appeal is breadth: one always-on gateway can become the front door to many daily actions, reminders, file operations, scheduled tasks and connected services.
Hermes is better understood as a developer-oriented agent that becomes more useful as it learns repeatable ways to do your work. Cloudways emphasizes persistent memory, reusable skills, terminal access and flexible execution. That can suit software work, research, repeatable technical procedures and workflows where the agent should retain methods rather than behaving mainly as a chat assistant. Messaging is still available, but it is not the only reason to choose Hermes.
The correct choice is therefore behavioral before it is technical. If you primarily want to message an agent from several channels and give it a wide assistant role, start by evaluating OpenClaw. If the attraction is a persistent technical agent that learns procedures, writes reusable skills and works deeply with terminal or code-oriented tasks, evaluate Hermes. The dedicated comparison page in this plugin turns those differences into a guided decision.
How to choose Scout, Operator, Squad or Swarm
Cloudways positions Scout for light checks and one or two simple workflows. That makes it suitable for testing, personal experimentation and an agent that spends much of the day idle. The mistake is assuming the lowest tier is automatically right because a single user owns the agent. A single user can still create a demanding workload if several channels, browser tasks, scheduled jobs, large local files or multiple sub-agents are active at the same time.
Operator is the more comfortable default for a genuinely active agent. Its 4 GB of RAM and 2 vCPUs provide more room for overlapping tasks, logs and helper processes. Squad is where multiple workflows or coordinated sub-agents become a normal part of the design rather than an occasional burst. Swarm is for heavy continuous use, where the cost of an under-sized agent shows up as queueing, slow task completion, memory pressure or constant monitoring rather than just a slightly higher hosting bill.
The sensible way to size is to start with the smallest tier that has clear headroom for your normal workload, then observe actual resource use over several days. Cloudways itself advises looking at usage over time rather than reacting to one short spike. The calculator on this page deliberately weights concurrency, sub-agents, channels and runtime pattern because those factors are more useful than choosing a plan only from the number of people who will talk to the agent.
The real monthly cost includes the model provider
The Cloudways plan price is the infrastructure portion of the budget. The agent still needs a model, and Cloudways uses a bring-your-own-key approach. If you connect OpenAI, Anthropic, Google or another supported provider, that provider bills your usage separately. A Scout server can therefore cost less than the model traffic generated by a busy workflow, while a Swarm server may still be a small part of the total if the agent processes large contexts or uses premium models continuously.
This separation is actually useful because it keeps infrastructure and model choice independent. You can choose a server tier based on CPU, memory and storage, then manage model cost through routing, model selection, prompt design, caching and task policies. Do not treat a cheap server price as a guarantee of a cheap AI system. A better budget has three lines: Cloudways infrastructure, LLM/API consumption, and any paid external tools or data services the agent calls.
For planning, start with the standard Cloudways monthly price and create a separate model allowance based on expected requests. If Cloudways is running an eligible Managed AI Agents promotion, calculate that as a discount on the infrastructure line only. The pricing calculator page in this cluster intentionally does not guess token usage because model rates, context sizes and workflow behavior vary too much for a single honest estimate.
Messaging channels change how an agent is used
Cloudways supports external communication channels so an agent can be reached without keeping its dashboard open. That matters because an agent connected to WhatsApp, Slack, Discord or Telegram becomes part of a real communication workflow rather than a demo interface. It can receive requests where a team already works, return results there and remain available from a phone. The operational benefit is convenience, but the security consequence is that channel permissions now become part of the agent boundary.
Each connected channel can also change the sizing profile. A dashboard-only agent used by one person may have long idle periods. The same agent connected to several team channels can receive overlapping requests, scheduled messages and automated events. That is why the calculator adds weight as the number of channels rises. It is not claiming that a channel consumes a fixed amount of RAM; it is recognizing that more entry points usually create more concurrent activity and more state to manage.
When connecting a channel, use the smallest permissions that allow the intended workflow. Keep bot tokens and API credentials out of public documentation, screenshots and source repositories. For business use, decide whether the agent may act on every message or only on explicit commands, and separate informational tasks from actions that change data. Convenient access should not become an accidental path to broad production control.
MCP can turn the hosted agent into an infrastructure operator
Cloudways also allows a Managed AI Agent to connect to MCP servers, including the Cloudways MCP server. That creates an interesting loop: the agent is hosted on Cloudways and can also gain structured access to Cloudways infrastructure tools. This can be useful for monitoring, deployment support, backups and other operational tasks, especially when combined with a persistent agent that already knows the project context.
The capability is powerful enough that permissions deserve deliberate design. Start with read-oriented tasks where possible, such as listing infrastructure or reviewing status, before giving an agent permission to restart services, deploy code, modify security settings or change paid resources. If you already installed Cloudzat Cloudways MCP Authority, use those client and permission guides as the separate infrastructure-control layer rather than overloading one page with every MCP detail.
For teams, consider separating the agent that talks to users from the credentials that can change infrastructure. A general assistant may need broad context but only read access, while a dedicated operations agent can have a narrower set of write permissions and a more controlled prompt. Managed hosting removes server-maintenance work, but it does not remove the need for access boundaries when AI is given tools that can make real changes.
Who should buy Managed AI Agent Hosting and who should self-host
Cloudways makes the strongest case for people who value time, predictable operations and a supported deployment path more than maximum low-level control. An agency can create a persistent agent without assigning someone to patch the host. A founder can test an automation idea without turning the experiment into a Linux administration project. A developer can still use terminal access while outsourcing the repetitive infrastructure layer. Those are practical advantages, not just convenience marketing.
Self-hosting still makes sense when you need a custom operating-system stack, unusual networking, specialized hardware, deep observability, a specific container topology or a hosting environment that Cloudways does not expose. It can also be appropriate when you already operate reliable infrastructure and adding another managed platform would increase complexity rather than reduce it. The cheapest VPS on a price table is not automatically cheaper once engineering time is included, but managed hosting is not automatically best either.
Use the decision in reverse: identify the work you do not want to own. If patching, backups, provisioning and routine host maintenance are distractions, Cloudways is worth evaluating. If those are already automated and your priority is absolute control, self-hosting may remain the better fit. For most affiliate comparisons, that distinction is more useful than declaring one platform the universal winner.
Methodology and primary sources
Cloudzat bases plan resources, pricing, deployment requirements and supported workflow claims on current Cloudways product and help-center documentation. Last verification date: August 26, 2026.
- Cloudways Managed AI Agents getting-started guide
- Cloudways Managed AI Agent instance sizing guide
- Cloudways OpenClaw managed hosting
- Cloudways Hermes managed hosting
- Cloudways Managed AI Agents general availability announcement
- Cloudways communication channels guide
- Cloudways MCP connection guide for Managed AI Agents
Frequently asked questions
Does Cloudways host both OpenClaw and Hermes?
Yes. Cloudways Managed AI Agents currently supports OpenClaw and Hermes. You select the agent when deploying the instance, then choose the region and server size and connect your own supported LLM provider.
What is the cheapest Cloudways AI Agent plan?
Scout is the entry tier at a standard published price of $9.99 per month, with 1 vCPU, 2 GB RAM and 50 GB SSD storage. It is intended for light usage, testing and simple workflows rather than heavy concurrent automation.
Are OpenAI or Anthropic API charges included?
No. Cloudways hosts the agent infrastructure, while your model provider bills model usage separately. Budget for the Cloudways instance and the LLM/API consumption as two different cost lines.
Can I use WhatsApp or Slack with a Cloudways AI agent?
Cloudways documents communication-channel support including WhatsApp, Slack, Discord and Telegram for its Managed AI Agents. Exact setup steps and supported fields can differ by agent, so check the Channels area for the deployed agent.
Can a Cloudways Managed AI Agent use MCP?
Yes. Cloudways documents connecting MCP servers from the Managed AI Agents area. MCP can expose external tools and APIs to the agent, so use scoped credentials and cautious write permissions.
Should I start with Scout or Operator?
Start with Scout for light testing or one or two simple workflows. Choose Operator when the agent will be active every day, handle overlapping tasks or needs more headroom. Monitor real usage and scale from evidence rather than guesswork.
Cloudzat may earn a commission if you sign up for Cloudways through links on this page. This does not change your price. Managed AI Agent features, integrations, plan resources, model-provider costs and promotions can change, so confirm critical details in Cloudways before purchase or production deployment.