OpenClaw Integration

MCTL includes OpenClaw as a managed platform service — a personal AI assistant that connects to messaging channels (Telegram, Discord, Slack, WhatsApp, and others) and can interact with your infrastructure through MCTL.

What is OpenClaw?

OpenClaw is an open-source personal AI assistant that runs on your own infrastructure. It answers on channels you already use (Telegram, Discord, Slack, WhatsApp, and 20+ others), supports voice, and provides a web-based Canvas UI.

MCTL maintains a fork (mctl-openclaw) that integrates OpenClaw with the platform:

• MCTL OAuth: seamless sign-in through the platform's authentication system
• Incident webhooks: the mctl-agent can dispatch incidents to OpenClaw for collaborative remediation
• Platform-aware sessions: OpenClaw sessions are scoped to GitHub-authenticated users
• Managed deployment: provisioned and scaled through MCTL MCP tools and GitOps

Architecture

Messaging Channels (Telegram, Discord, Slack, ...)
        |
        v
   OpenClaw Gateway  <--- mctl-agent (incident webhooks)
        |
        v
   AI Model (OpenAI, Anthropic, etc.)
        |
        v
   Skills & Tools (including MCTL MCP tools)

OpenClaw runs as a gateway service in your tenant namespace. It connects to your messaging channels and routes conversations through an AI model. The platform handles deployment, scaling, database provisioning, and secret management.

Deploying OpenClaw

Via MCP

"Deploy OpenClaw for my-team"

This calls mctl_deploy_openclaw, which:

1. Prepares the deployment configuration
2. Returns a Telegram bot-token intake URL
3. After you provide the bot token, call:

   "Resume the OpenClaw deployment for my-team"

4. MCTL provisions a PostgreSQL database and deploys the gateway

What gets provisioned

Resource	Description
Deployment	OpenClaw gateway container
Database	PostgreSQL on shared CNPG cluster
Secrets	Bot tokens, API keys stored in Vault
Ingress	HTTPS endpoint for the web UI and webhook callbacks

Resource Optimization

OpenClaw can consume significant resources depending on usage patterns. MCTL provides tools to right-size your deployment:

Get sizing recommendations

"Get resource sizing recommendations for openclaw in my-team"

This calls mctl_get_openclaw_sizing_recommendation, which analyzes VictoriaMetrics history and suggests an optimal resource profile.

Apply a resource profile

"Apply the steady-small resource profile to openclaw in my-team"

Available profiles:

Profile	CPU Request	Memory Request	Use case
startup	500m	512Mi	Initial deployment, testing
steady-medium	250m	384Mi	Regular usage, multiple channels
steady-small	100m	256Mi	Low traffic, single channel

Incident Integration

The mctl-agent can dispatch incidents to OpenClaw for collaborative remediation:

1. AlertManager fires an alert
2. mctl-agent creates an incident ticket and selects a skill
3. If the skill requires external assistance, the agent sends a signed webhook to OpenClaw
4. OpenClaw creates a scoped session for the incident
5. The AI model analyzes the incident and proposes a fix
6. Results are sent back to mctl-agent via callback
7. mctl-agent creates a PR to mctl-gitops with the fix

This integration enables multi-agent remediation where the platform agent and the personal assistant collaborate on incident resolution.

Fork Maintenance

mctl-openclaw tracks upstream openclaw/openclaw with a weekly sync workflow:

• A GitHub Actions workflow creates a sync/upstream-YYYY-MM-DD branch
• The sync PR is tested in the labs-openclaw tenant before promotion
• Fork-specific patches are maintained as a thin layer on top of upstream

Fork-specific areas reviewed on each sync:

• OAuth and gateway behavior
• Webhook automation and session creation
• Whisper/runtime packaging
• Platform-specific deployment assumptions

Useful Links

• OpenClaw documentation
• OpenClaw GitHub
• MCTL MCP Tools Reference — see the OpenClaw section