Deploy OpenClaw and Connect It to Your Infrastructure in Minutes with Clanker Cloud

OpenClaw is one of the most capable autonomous AI agents available right now — 68,000+ GitHub stars, support for GPT-5.4, Claude Opus/Sonnet, Gemini 3.1, and any Ollama model, plus a 13,700-skill library on ClawHub. Out of the box it can answer questions, write code, run tasks on a schedule, and push updates to Slack, Telegram, WhatsApp, or Discord.

The missing piece, for infrastructure teams, is live context. Without a connection to your actual running resources, OpenClaw works from whatever information you paste into the conversation. It can reason about infrastructure, but it cannot observe it.

Clanker Cloud closes that gap. Its built-in MCP endpoint exposes your live DigitalOcean environment — droplets, databases, app platform deployments, load balancers — as a set of tools OpenClaw can call in real time. Once connected, OpenClaw becomes an autonomous infrastructure agent: one that checks service health every 30 minutes, flags spend anomalies, scans for misconfigs, and reports to your team via the channel they already use.

This guide covers both deployment paths — running OpenClaw on a dedicated DigitalOcean droplet via 1-Click, or using Clanker Cloud to provision the droplet itself — then configures the Clanker Cloud MCP integration that ties it together. If you have been looking for a reason to move from vibe coding to production, this setup delivers it.

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OpenClaw + Live Infrastructure Context = a Genuinely Autonomous Agent

OpenClaw's HEARTBEAT.md mechanism runs a task checklist every 30 minutes. You define the checks; OpenClaw executes them and escalates when something needs attention. That is useful on its own, but each check is only as valuable as the data behind it.

With Clanker Cloud registered as an MCP skill, every HEARTBEAT check can query your live environment. OpenClaw can ask "What is the current error rate on the production API?" and Clanker Cloud MCP responds with real data. It can pull current monthly spend, list running droplets, or check whether any security group is misconfigured — without you copying dashboards into a prompt.

This is the difference between an agent that knows about infrastructure in general and one that knows about your infrastructure specifically.

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Two Deployment Paths

Path A — DigitalOcean 1-Click deploy. Use DigitalOcean Marketplace to spin up a pre-configured OpenClaw droplet in one click, then register Clanker Cloud as an MCP skill. Fastest path from zero to running agent.

Path B — Clanker Cloud deploys the droplet. Use Clanker Cloud itself to provision the DigitalOcean droplet that will host OpenClaw. This is the recursive case: Clanker Cloud manages the infrastructure that OpenClaw then monitors. A good way to see Clanker Cloud's maker mode before OpenClaw is even running.

Both paths end with the same Clanker Cloud MCP configuration. If you already have OpenClaw running locally, skip to the MCP configuration section.

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Path A: DigitalOcean 1-Click Deploy

The DigitalOcean Marketplace lists a pre-configured OpenClaw 1-Click app. The droplet ships with OpenClaw installed and ready to configure — no manual Node.js setup.

Step 1: Launch the droplet

Go to the DigitalOcean Marketplace and search for OpenClaw. A $6/mo droplet (1 vCPU, 1 GB RAM) handles light workloads. Step up to $12/mo (1 vCPU, 2 GB RAM) if you plan to run a local Ollama model on the same instance. Deploy to the region closest to your existing infrastructure — latency matters when MCP calls are in the loop.

Step 2: SSH in and configure OpenClaw

ssh root@<your-droplet-ip>

# Set your model and API key
openclaw config set model gpt-5.4
openclaw config set openai-api-key <your-key>

# Or use Claude
openclaw config set model claude-opus
openclaw config set anthropic-api-key <your-key>

Step 3: Connect your messaging channel

# Slack
openclaw channel add slack --token xoxb-<your-bot-token> --channel #ops-alerts

# WhatsApp for personal on-call
openclaw channel add whatsapp --token <your-twilio-token>

Step 4: Register Clanker Cloud as an MCP skill

# Local Clanker Cloud instance
openclaw mcp set clanker-cloud --url http://localhost:39393

# Or remote endpoint
openclaw mcp set clanker-cloud --url https://your-clanker-mcp-endpoint

Step 5: Verify the connection

openclaw ask "List all running droplets via clanker-cloud"

A live list of your DigitalOcean resources confirms the MCP integration is working.

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Path B: Clanker Cloud Deploys the Droplet

This path uses Clanker Cloud to provision the DigitalOcean droplet that will host OpenClaw — a good demonstration of maker mode before the agent is running.

Step 1: Install Clanker Cloud and connect DigitalOcean

Download the desktop app from clankercloud.ai/account. On first launch, connect your DigitalOcean account. Clanker Cloud is local-first — your credentials stay on your machine. The underlying CLI is open source at github.com/bgdnvk/clanker.

Step 2: Provision the droplet

In the Clanker Cloud workspace:

"Provision a new Ubuntu 22.04 droplet in nyc3, 1 vCPU, 2 GB RAM, for running an OpenClaw agent. Name it openclaw-prod."

Clanker Cloud enters maker mode: generates a plan with estimated cost and configuration, waits for your approval, then provisions the droplet in under two minutes.

Step 3: Install OpenClaw

ssh root@<new-droplet-ip>

# Install Node.js 20+
curl -fsSL https://deb.nodesource.com/setup_20.x | bash -
apt-get install -y nodejs

# Install OpenClaw globally
npm install -g openclaw

Step 4: Configure and connect

openclaw config set model claude-sonnet
openclaw config set anthropic-api-key <your-key>
openclaw channel add slack --token xoxb-<your-bot-token> --channel #ops-alerts
openclaw mcp set clanker-cloud --url http://localhost:39393
openclaw ask "What databases are currently running via clanker-cloud?"

You now have Clanker Cloud managing the droplet and OpenClaw running on it, using Clanker Cloud as its live data source. The same tool that provisioned the infrastructure feeds the agent monitoring it. This pairs naturally with AI DevOps for teams workflows.

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Configuring the Clanker Cloud MCP Integration

Whether you used Path A or Path B, the MCP configuration is identical.

# Register Clanker Cloud as an OpenClaw MCP skill
openclaw mcp set clanker-cloud --url http://localhost:39393

# Remote endpoint variant
openclaw mcp set clanker-cloud --url https://your-clanker-mcp-endpoint

# Confirm registration
openclaw mcp list

Once registered, OpenClaw can call these Clanker Cloud MCP tool categories from any task or HEARTBEAT check:

• Resource listing — running droplets, databases, load balancers, app platform deployments
• Health queries — service status, uptime, error rates
• Cost reporting — current spend, period-over-period comparison, anomaly detection
• Security scanning — misconfigured firewall rules, open ports, overpermissioned API keys

You do not configure capabilities individually. Registering the endpoint exposes all of them; OpenClaw discovers available tools via MCP and routes calls based on task context.

For teams with multiple environments, register each as a named skill:

openclaw mcp set clanker-prod --url https://prod-clanker-mcp-endpoint
openclaw mcp set clanker-staging --url https://staging-clanker-mcp-endpoint

Reference them explicitly in HEARTBEAT tasks to keep monitoring scoped to the right environment.

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Setting Up HEARTBEAT.md for Autonomous Monitoring

HEARTBEAT.md is a markdown file in your OpenClaw working directory. OpenClaw reads it on a 30-minute loop and executes each unchecked task, marking items complete or escalating when attention is needed.

# HEARTBEAT

## Every 30 minutes
- [ ] Check health of all production services via clanker-cloud — report any with error rate > 1% to #ops-alerts
- [ ] List droplets running > 7 days without a snapshot — flag to #ops-alerts
- [ ] Confirm all load balancers are active and healthy

## Every day at 9am
- [ ] Run cost check via clanker-cloud — flag spend anomalies > 20% vs prior 7-day average
- [ ] Check for security misconfigs — open firewall rules, public database endpoints — summarize to #ops-alerts
- [ ] Confirm all database backups completed within the last 24 hours

## Every week
- [ ] Generate infrastructure summary: resources, cost breakdown, health status — post to #ops-weekly
- [ ] Identify idle or underutilized droplets — recommend for downsizing or termination

Save to ~/openclaw/HEARTBEAT.md. Watch it execute with openclaw logs --follow.

The value here is zero-touch monitoring. Set the checks once; they run indefinitely. If a service degrades at 3am, OpenClaw catches it on the next cycle and pushes the alert to Slack before anyone checks their phone. For AI DevOps for teams setups, this replaces a layer of alert wiring that would otherwise require dedicated tooling.

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Choosing the Right Model

OpenClaw supports several model backends. The right one depends on workload and cost tolerance.

GPT-5.4 is the default. Strong for complex HEARTBEAT tasks involving judgment calls — flagging spend anomalies, assessing misconfiguration severity.

Claude Opus/Sonnet works well for teams already on Anthropic. Sonnet in particular is fast and cost-efficient for high-frequency 30-minute checks.

Gemini 3.1 is a solid option if you are running Google Cloud alongside DigitalOcean.

Gemma 4 via Ollama eliminates per-query API cost entirely. Install it on the same droplet:

curl -fsSL https://ollama.com/install.sh | sh
ollama pull gemma4

openclaw config set model ollama/gemma4
openclaw config set ollama-endpoint http://localhost:11434

A $12/mo droplet running Gemma 4 handles routine monitoring tasks with zero ongoing API spend. Use --model on specific tasks to route complex reasoning to a cloud model while keeping routine checks local. Clanker Cloud also supports Gemma 4 via Ollama as a BYOK option, so the full stack can run without cloud model dependencies.

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Multi-Channel Setup

OpenClaw delivers infrastructure alerts wherever your team actually watches.

Slack is the natural fit for most engineering teams — route critical alerts to #ops-alerts and weekly summaries to #ops-weekly.

openclaw channel add slack \
  --token xoxb-<your-bot-token> \
  --channel #ops-alerts \
  --alias ops-alerts

Telegram or WhatsApp works for personal on-call setups — useful for solo founders or small teams who want phone alerts without a full PagerDuty integration.

openclaw channel add telegram \
  --token <your-bot-token> \
  --chat-id <your-chat-id>

Discord fits developer communities or open-source projects where infrastructure status matters to contributors.

All channels use the same Clanker Cloud-sourced data. OpenClaw calls the MCP endpoint once and formats the output for each destination — adding or removing channels does not require changes to your HEARTBEAT configuration.

See the for AI agents overview and demo for more on Clanker Cloud's agent-facing capabilities.

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FAQ

How do I deploy OpenClaw to DigitalOcean?

The fastest path is the DigitalOcean Marketplace 1-Click app. Search for OpenClaw, choose your droplet size, and deploy. OpenClaw is pre-installed; SSH in and configure your API keys and channel integrations. To manage the provisioning yourself, use Clanker Cloud's maker mode to create the droplet, then install OpenClaw with npm install -g openclaw.

How do I connect OpenClaw to my cloud infrastructure?

Register Clanker Cloud as an MCP skill: openclaw mcp set clanker-cloud --url <your-clanker-mcp-endpoint>. That single command gives OpenClaw access to live infrastructure state — running resources, service health, spend, security configuration — all via Clanker Cloud's MCP server. No custom integration code needed.

What is the HEARTBEAT.md file in OpenClaw?

HEARTBEAT.md is a markdown checklist OpenClaw reads and executes every 30 minutes. Each item is a task OpenClaw attempts — checking service health, running cost reports, sending Slack alerts. Connected to Clanker Cloud via MCP, HEARTBEAT checks query live data instead of static context. Define the checklist once; OpenClaw runs it continuously.

Can OpenClaw monitor my AWS or Kubernetes infrastructure automatically?

Clanker Cloud currently covers DigitalOcean: droplets, managed databases, app platform, and load balancers. For AWS or Kubernetes, you would need a compatible MCP server exposing those resources, then register it as a separate OpenClaw skill alongside Clanker Cloud. OpenClaw supports multiple concurrent MCP skills, so mixed-cloud setups work at the agent configuration level.

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Get Started

The setup described here — OpenClaw on DigitalOcean, connected to Clanker Cloud MCP, running autonomous HEARTBEAT checks — takes under an hour from scratch. The 1-Click path is faster. The Clanker Cloud provisioning path shows you more of what both tools can do.

Either way, you end up with an OpenClaw infrastructure agent that has live context about your environment, reports to your team automatically, and requires no ongoing configuration work. The Clanker Cloud MCP connection is what makes that possible.

• Create your account: clankercloud.ai/account
• Full documentation: docs.clankercloud.ai
• OpenClaw + AI agents: /for-ai-agents.md
• See it in action: /demo
• Common questions: /faq