@clawops/cli

clawops

MCP-native infrastructure ops for OpenClaw — with read-only mode, destructive-action confirmation, and audit logs built in.

clawops is a CLI and MCP server for deploying and operating self-hosted OpenClaw instances. Provision on AWS, GCP, Azure, or any Linux VM — then manage day-to-day operations from the terminal, or let Claude Code and Cursor drive them through typed MCP tools with explicit safety controls.

What's new in v1.7.0

clawops harden — run an idempotent set of server-hardening modules against a deployed stack over SSH. Each module has a read-only check() and an apply() step; check() runs first and apply() is skipped when the box is already compliant. Sentinel files under /etc/clawops/hardening/ record what has been applied.

clawops harden --list                          # show available modules
clawops harden --stack prod --dry-run          # preview changes, apply nothing
clawops harden --stack prod                     # apply the default module set
clawops harden --stack prod --options ssh,ufw   # apply a specific subset

Common modules (all providers), ON by default: ssh (hardens sshd_config, guards against lockout by verifying authorized_keys is non-empty before restarting sshd), ufw (deny-all incoming, allow SSH + gateway 18789), fail2ban (SSH jail: 5 failures → 10-minute ban), unattended-upgrades (security-only auto updates), and docker-socket (verify /var/run/docker.sock is root:docker 660). Opt-in: auditd, lynis (CIS Level 1 scan → ~/.clawops/reports/), sysctl.

AWS modules (check-only, ON by default): aws-sg-audit (warns on 0.0.0.0/0 ingress on unexpected ports) and aws-ssm-check (verifies AmazonSSMManagedInstanceCore for emergency SSM shell access). Opt-in: aws-flow-logs, aws-guardduty.

clawops setup now presents a multi-select hardening step after deploy (skippable with --no-harden), and clawops doctor --stack <name> gains a Hardening section showing which modules are applied, missing, or drifted.

What's new in v1.6.0

clawops bug — open a pre-filled GitHub issue with system context (version, Node, OS, provider, stack count, SSH key presence) populated automatically. --json emits the URL without prompting or opening a browser, suitable for scripting. clawops doctor now prints a clawops bug hint in its footer when it exits with an error.

clawops bug              # open a pre-filled issue in the browser
clawops bug --json       # print the issue URL for scripting

Cloud deploy bug fixes (AWS, GCP, Azure). This release fixes 10 bugs found in a deploy audit, several deploy-blocking:

• Azure: updated deprecated image reference UbuntuServer/22.04-LTS → 0001-com-ubuntu-server-jammy/22_04-lts-gen2 — every Azure deployment was broken; and fixed a malformed Key Vault roleDefinitionId that broke Key Vault RBAC entirely.
• AWS: Bedrock startup script now uses the IMDSv2 PUT→GET token flow (a plain curl to IMDS returned 401, so the region always fell back to us-east-1); replaced AmazonBedrockFullAccess with a least-privilege inline policy.
• AWS (⚠️ migration impact): migrated from inline Security Group ingress/egress arrays to individual SecurityGroupIngressRule/SecurityGroupEgressRule resources so CIDR changes no longer replace the whole Security Group. Existing AWS stacks have their Security Group replaced on the first clawops up after this upgrade — see docs/decisions/0009-aws-sg-rule-resources.md for the import-based mitigation.
• All providers: accessMode=auto egress-IP detection now returns a Result and throws a clear error on failure instead of silently producing a VM with zero ingress rules.

What's new in v1.5.0

clawops mcp wire — wire the OpenClaw gateway's own AI as an MCP client of clawops. Once wired, in-conversation commands like "check if my stack is healthy" or "show me the last 20 log lines" invoke the real clawops CLI rather than having the gateway AI guess.

clawops mcp wire                   # wire the default stack
clawops mcp wire --stack prod      # target a named stack
clawops mcp wire --force           # bypass gateway version check

Version-gated: requires OpenClaw ≥ 2026.4 on the gateway side. If the version is older, the command surfaces a clear upgrade prompt and exits cleanly.

The clawops setup wizard now also asks at the end of a successful deploy: "Should the OpenClaw gateway's AI also be able to manage this stack?" — accepting wires the client automatically over the same SSH session.

What's new in v1.4.0

clawops monitor — live dashboard for any deployed stack. Shows gateway health, container status, CPU/memory, disk usage, and a rolling log tail. Refreshes on an interval with [r], toggles logs with [l], and quits with [q].

Run without --stack to get an interactive stack picker first — probes all registered stacks in parallel, shows only running ones by default, and lets you toggle to a full list ([a]) where not-deployed stacks can be deleted from the registry with [d]. Press [s] inside the dashboard to go back to the picker.

clawops monitor              # interactive stack selection → dashboard
clawops monitor --stack prod # jump straight to a named stack
clawops monitor --stack prod | cat  # one-shot snapshot for CI

clawops_monitor MCP tool — same snapshot as a single structured JSON call, so Claude Code and Cursor can check stack health without opening a terminal.

clawops stacks delete guard — now blocks deletion of a still-deployed stack and requires --force to remove from the registry without tearing down cloud resources first.

Who this is for

• OpenClaw users who want the simplest path to self-hosting across cloud or local VMs, with reliable deploy, status checks, logs, backups, and upgrades in a single CLI.
• Claude Code / Cursor / MCP users looking for a real-world reference implementation of safe infrastructure operations through MCP — typed tool schemas, read-only mode, destructive-action confirmation, and audit logs.
• Self-hosted AI and local-first developers who want to run their own AI assistant without committing to Kubernetes, a managed SaaS platform, or a single cloud provider.

What clawops does

• Provisions and tears down OpenClaw infrastructure on AWS, GCP, Azure, and local VMs using the Pulumi Automation API (embedded — no pulumi binary required).
• Manages day-to-day operations: status, logs, SSH, tunnels, config, agents, gateway, backups.
• Exposes every operation as a typed MCP tool so AI agents can drive ops safely.
• Enforces a plan → review → apply discipline for cloud deployments.
• Emits JSON output everywhere (--json) for scripting and automation.
• Never stores cloud credentials — reads them from your environment's existing CLI profiles.

What clawops does not do

• No high availability or clustering. Optimized for single-node deployments.
• No Kubernetes. It deploys to VMs, not container orchestration platforms.
• No OpenClaw skill/agent authoring. clawops manages infrastructure; what runs on it is up to you and OpenClaw.
• No TLS or domain automation (yet). Bring your own reverse proxy or see docs/limitations.md for the manual path.
• No credential storage. Cloud credentials must be configured in your environment before using clawops. They are never written to ~/.clawops/config.json.
• No native Windows. WSL2 is fully supported; see docs/support-matrix.md.

Quick Start

npm install -g @clawops/cli
clawops setup

clawops setup is an interactive wizard that gets OpenClaw running in about 2 minutes. It handles everything in one flow — no config files to write by hand, no commands to memorize.

What the wizard does

Step 1 — Choose a deployment target

Pick an existing server you can SSH into (Linux or macOS), or a new cloud VM on AWS, GCP, or Azure. Cloud deployments walk you through authenticating with the provider CLI if you aren't already signed in.

Step 2 — Pick an LLM provider

Choose from Anthropic, OpenAI, Amazon Bedrock, Ollama, or others. The wizard prompts for your API key and saves it locally (in ~/.clawops/secrets/, chmod 600) — it is never sent anywhere except to OpenClaw on the target host when the config is applied.

Step 3 — Add chat integrations (optional)

Select any combination of Discord, Telegram, Slack, WhatsApp, or Teams. The wizard collects each integration's bot token the same way as the API key — paste it in, reference an env var, or point to a file.

Step 4 — Wire your AI editor

Select which AI apps should have access to clawops — Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, and Zed are all supported. The wizard writes an MCP server entry into each app's config file using the absolute binary path so the app can launch it independently.

Step 5 — Deploy

The wizard bootstraps OpenClaw on the target host over SSH (installs Docker, pulls the image, starts the container), applies your LLM and integration config, generates a gateway auth token, and prints a direct dashboard URL:

✔ All done! OpenClaw is running.
ℹ Open dashboard: http://192.168.1.50:18789?token=<your-token>
ℹ Token saved to ~/.clawops/secrets/GATEWAY_TOKEN_my-stack

Prerequisites: Node.js ≥ 22, an SSH key, and either an SSH-reachable Linux/macOS host or a cloud account with CLI credentials configured (aws configure, gcloud auth login, or az login).

For a full narrated walkthrough with example output, see docs/demo-script.md.

Manual setup — existing server

If you prefer step-by-step control, or are adding clawops to an already-running deployment:

npm install -g @clawops/cli

clawops doctor   # verify environment

clawops init --provider local --host 192.168.1.50 --user ubuntu --key-path ~/.ssh/id_ed25519
clawops up       # installs Docker + OpenClaw over SSH
clawops status

See docs/examples/local-vm.md for SSH prerequisites, firewall setup, and troubleshooting.

Manual setup — cloud (AWS)

npm install -g @clawops/cli

# Requires AWS credentials in your environment (AWS_PROFILE or ~/.aws/credentials)
clawops init --provider aws

# Edit ~/.clawops/config.json — set stateUrl to your S3 bucket

clawops plan --provider aws --stack default --out /tmp/plan.json
clawops apply /tmp/plan.json

Connect an AI editor

The setup wizard handles this automatically (Step 4). To wire or re-wire editors at any time:

clawops mcp install

This opens the same interactive checkbox used in the wizard — select Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, or Zed and clawops writes the MCP entry into each app's config using the correct absolute binary path.

To add the entry manually instead, paste this into your editor's MCP config:

{
  "mcpServers": {
    "clawops": {
      "command": "/path/to/clawops",
      "args": ["mcp", "serve", "--read-only"]
    }
  }
}

Replace /path/to/clawops with the output of which clawops. Config file locations:

App	Path
Claude Desktop (macOS)	~/Library/Application Support/Claude/claude_desktop_config.json
Claude Desktop (Linux)	~/.config/Claude/claude_desktop_config.json
Claude Code	~/.claude.json
Cursor	~/.cursor/mcp.json
Windsurf	~/.codeium/windsurf/mcp_config.json
VS Code (macOS)	~/Library/Application Support/Code/User/mcp.json
VS Code (Linux)	~/.config/Code/User/mcp.json
Zed	~/.config/zed/settings.json (key: context_servers)

Start with --read-only — it enables status, logs, config reads, and diagnostics while blocking mutations. Remove it only after reviewing docs/security/mcp-safety.md.

Destructive tools (clawops_destroy, clawops_up, clawops_config_set, etc.) require explicit confirmation before executing — they will never run silently.

For HTTP mode setup see docs/mcp/.

Day-to-day operations

clawops status              # Stack outputs: IP, gateway URL, SSH info
clawops logs -f             # Tail OpenClaw logs over SSH
clawops ssh                 # Interactive SSH session
clawops ssh --command "docker ps"

clawops config get maxAgents
clawops config set maxAgents 8

clawops tunnel              # Port-forward gateway UI to localhost

clawops destroy --yes       # Destroy cloud-provider stack
clawops down --yes          # Destroy local-provider stack

Commands

Command	Description
setup	First-run wizard — guided LLM, integrations, and deploy-plan generation
init	Register a stack in ~/.clawops/config.json without provisioning
up	Provision or update stack (--dry-run for preview)
down	Destroy local-provider stack (requires --yes; --dry-run shows current outputs)
destroy	Destroy cloud-provider stack with confirmation prompt (--dry-run shows current outputs)
status	Show stack outputs: IP, gateway URL, region, provisioned time
plan	Generate a deploy-plan JSON artifact (dry-run safe)
apply	Apply a previously reviewed plan file (--dry-run validates and shows diff without applying)
ssh	Interactive SSH session or run a remote command
logs	Stream OpenClaw logs (-f, --tail N, --since 5m)
tunnel	Local port-forward to gateway UI over SSH
config	Get/set remote OpenClaw config values (--dry-run shows would-write JSON)
agents	List or restart OpenClaw agents
gateway	Restart the OpenClaw gateway service
backup	Create or restore an OpenClaw state backup
stacks	List named stacks and their state
doctor	Check Node version, config, SSH key, provider credentials, and Pulumi home
secret	Manage secrets: list, set, delete, rotate, audit
monitor	Live dashboard: gateway health, container stats, log tail, stack picker
mcp serve	Start the embedded MCP server (stdio or HTTP)
mcp install	Interactively wire clawops into AI editors
mcp wire	Wire the gateway's AI as an MCP client of clawops
help	List all commands and global flags
harden	Apply security hardening to a deployed stack (SSH, UFW, fail2ban, unattended-upgrades, Docker socket; AWS: SG audit, SSM check, Flow Logs, GuardDuty)
bug	Open a pre-filled GitHub issue with system context from doctor

Full flag reference: clawops <command> --help

Plan → Apply workflow

For non-local providers, clawops enforces a review-before-apply discipline:

# 1. Generate a plan — runs `pulumi preview` internally, produces JSON
clawops plan --provider aws --region us-east-1 --out /tmp/plan.json

# 2. Review plan.json — the `diff` field shows projected changes at plan-generation time
cat /tmp/plan.json | jq .diff

# 3. Apply — reads and validates the plan file, then runs `pulumi up`
clawops apply /tmp/plan.json

# Without --yes, apply prompts: "Continue? (y/N)"
clawops apply /tmp/plan.json --yes    # skip prompt in automation

The plan JSON conforms to spec/deploy-plan.schema.json (AJV-validated) and captures reviewed intent: provider, region, instance type, CIDR ranges, and OpenClaw version. apply re-runs pulumi up using those parameters against the current live state — it does not replay a locked execution artifact. Review and apply in the same session to minimize drift risk.

See docs/plan-apply.md for full semantics, drift guidance, and the safe CI pattern.

MCP server

clawops ships an embedded MCP server. Claude Code, Cursor, and any MCP-compatible agent can drive deployments without leaving the chat interface.

Wire your editor

clawops mcp install   # interactive checkbox — writes config for selected apps

The wizard resolves the absolute binary path automatically so app launchers can find clawops without inheriting your shell's PATH. See Connect an AI editor above for manual config paths.

Wire the gateway AI

The OpenClaw gateway runs its own AI agent. Once wired, that agent can call clawops directly instead of guessing at infrastructure state:

clawops mcp wire --stack prod   # write MCP client entry into gateway config + restart

Requires OpenClaw ≥ 2026.4 on the gateway. The clawops setup wizard offers this step automatically after a successful deploy.

Stdio mode (Claude Code / Cursor / VS Code)

Start the server manually or confirm your config is correct:

clawops mcp serve --read-only   # safe for first evaluation
clawops mcp serve               # full mode — enables provisioning, config write, ssh exec

HTTP mode (remote / multi-client)

clawops mcp serve --http 3333 --bind 127.0.0.1
# MCP HTTP server listening on 127.0.0.1:3333

Do not bind to a non-loopback address without additional authentication controls in front of it.

Available tools

Tool	Toolset	Description
clawops_status	read	Show stack outputs
clawops_logs_tail	read	Tail OpenClaw logs
clawops_config_get	read	Read a remote config value
clawops_agents_list	read	List running agents
clawops_task_status	read	Poll a long-running task
clawops_stacks_list	admin	List all stacks and their state
clawops_up	cli	Provision or update a stack
clawops_plan	cli	Generate a deploy plan
clawops_apply	cli	Apply a plan file
clawops_ssh_exec	cli	Run a command over SSH
clawops_config_set	cli	Write a remote config value
clawops_destroy	cli	Destroy a stack (elicits confirmation)
clawops_workflow_deploy_app	workflow	End-to-end deploy: plan → confirm → apply → status

read toolset tools are available in --read-only mode. All other toolsets require full mode. Destructive tools require explicit confirmation (elicitation) unless yes: true is passed.

See docs/security/tool-risk-matrix.md for the full risk classification of every tool.

Configuration

Config lives at ~/.clawops/config.json (override with $CLAWOPS_HOME).

{
  "version": 1,
  "defaults": {
    "provider": "aws",
    "stack": "default"
  },
  "stacks": {
    "default": {
      "provider": "aws",
      "region": "us-east-1",
      "stateUrl": "s3://my-clawops-state"
    }
  },
  "ssh": {
    "keyPath": "~/.clawops/id_ed25519",
    "knownHostsPath": "~/.clawops/known_hosts"
  }
}

Cloud credentials are never stored in config — clawops reads them from the environment:

Provider	Credential source
AWS	AWS_PROFILE or standard AWS credential chain (~/.aws/credentials)
GCP	GOOGLE_APPLICATION_CREDENTIALS or gcloud auth application-default login
Azure	AZURE_CLIENT_ID / AZURE_CLIENT_SECRET or az login
Local	SSH host + key configured in stacks[name].localOpts

Known limitations

See docs/limitations.md for the full list. Key points:

• Single-node deployments only — not a high-availability or clustering platform.
• clawops apply is not an immutable plan execution — see docs/plan-apply.md.
• No TLS/domain automation in the current release.
• MCP tools execute privileged operations — use --read-only for first evaluation.

Architecture

clawops
├── src/cli/          citty-based commands (one file per verb)
├── src/config/       ~/.clawops/config.json management
├── src/providers/    Cloud adapters (AWS, GCP, Azure, local)
│   ├── aws/          Pulumi inline program + ProviderAdapter
│   ├── gcp/
│   ├── azure/
│   └── local/        SSH bootstrap (no Pulumi)
├── src/pulumi/       Pulumi Automation API wrapper + output helpers
├── src/transport/    SSH client (ssh2) + connection pool + tunnels
├── src/mcp/          MCP server, tool handlers, progress tracking
├── src/plan/         Maker plan generation, AJV validation, apply
├── src/output/       ASCII table, spinner, JSON, human-readable output
├── src/errors/       Typed error hierarchy with exit codes
└── spec/             Machine-readable ground truth (JSON Schema, YAML)

Key design decisions:

• Pulumi Automation API (embedded): no pulumi binary required; Pulumi home is sandboxed to ~/.clawops/.pulumi; stack programs are inline TypeScript closures
• State in cloud blob storage: GCS (gs://), S3 (s3://), Azure Blob — no local state files, no pulumi.yaml
• SSH via ssh2: never shells out to /usr/bin/ssh; TOFU host verification against ~/.clawops/known_hosts; connection pool with 5-min idle TTL
• Plan → apply discipline: every non-local deployment goes through generatePlan() → review → applyPlan(); destructive changes always require human review of the plan JSON
• MCP-first: every CLI operation has a typed MCP tool; schemas generated from spec/mcp-tools.yaml; all destructive tools use elicitation

See docs/architecture.md for a full narrative, and docs/decisions/ for ADRs.

Cloud provider stacks

Each cloud provider is an inline Pulumi program that creates the resources below. All three share the same outputs (publicIp, gatewayUrl, sshHost, sshPort, sshUser) consumed by the SSH and config-overlay layers.

AWS

flowchart LR
    subgraph NET["Networking"]
        VPC["VPC (10.0.0.0/16)"]
        IGW[Internet Gateway]
        SUBNET["Subnet (10.0.1.0/24)"]
        RT[Route Table]
        SG["Security Group (ports 22, 18789)"]
    end
    subgraph IAM["IAM"]
        ROLE[IAM Role]
        SSM[SSM Policy Attachment]
        BED["Bedrock Policy Attachment (optional)"]
        IP[Instance Profile]
    end
    subgraph COMPUTE["Compute"]
        KP[EC2 Key Pair]
        EC2["EC2 Instance (Ubuntu 22.04, IMDSv2)"]
        EIP[Elastic IP]
    end

Detailed diagram →

GCP

flowchart LR
    subgraph NET["Networking"]
        NW[VPC Network]
        SN["Subnetwork (10.0.0.0/24)"]
        FW1["Firewall: SSH port 22 (conditional)"]
        FW2["Firewall: Gateway port 18789 (conditional)"]
        ADDR[Static External IP]
    end
    subgraph COMPUTE["Compute"]
        VM["Compute Instance (Debian 12, 20 GB)"]
    end

Detailed diagram →

Azure

flowchart LR
    RG[Resource Group]
    subgraph NET["Networking"]
        VNET["Virtual Network (10.0.0.0/16)"]
        SUBNET["Subnet (10.0.1.0/24)"]
        NSG["Network Security Group (ports 22, 18789)"]
        PIP["Public IP Address (Static)"]
        NIC[Network Interface]
    end
    subgraph COMPUTE["Compute"]
        VM["VM (Ubuntu 22.04, managed identity)"]
    end
    subgraph KV["Key Vault (optional)"]
        VAULT["Key Vault (RBAC, name max 24 chars)"]
        RA["Role Assignment (Secrets User)"]
        SECRET["Secret: gateway-token"]
    end

Detailed diagram →

Development

Setup

git clone https://github.com/dfridkin/clawops.git
cd clawops
# Node 22+ required; use nvm: nvm use
pnpm install
pnpm dev doctor        # verify toolchain

Scripts

pnpm dev                   # run CLI from src/ via tsx
pnpm build                 # tsup → dist/
pnpm test                  # vitest (493 tests, ~3s)
pnpm test:changed          # vitest --changed (fast edit loop)
pnpm test:integration      # Docker-based SSH integration tests
pnpm typecheck             # tsc --noEmit
pnpm lint                  # eslint src/ tests/ scripts/ (--max-warnings=0)
pnpm gen:schemas           # regenerate src/providers/types.ts + src/mcp/tools/_generated.ts
pnpm gen:schemas --check   # CI guard: committed generated files match spec
pnpm changeset             # record a release note before merging

Project layout

Path	Purpose
spec/	Machine-readable ground truth: JSON Schema, YAML. Treat as source of truth.
SPEC.md	Full technical specification (milestones, rules, schemas)
DESIGN_RULES.md	25 normative rules (R1–R25) referenced throughout the codebase
docs/architecture.md	Narrative system overview
docs/plan-apply.md	Plan/apply semantics, drift guidance, CI pattern
docs/ci.md	CI integration guide: OIDC, env vars, plan → apply in CI
docs/security/	MCP safety model, tool risk matrix, redaction, audit logs
docs/providers/matrix.md	Per-provider capability matrix
docs/decisions/	Architecture Decision Records
.claude/skills/	Invokable procedures: /add-provider, /release, /tdd, /mcp-tool
.claude/rules/	Path-scoped lint rules loaded by Claude Code

Code generation

Two files are generated from spec/ and must not be hand-edited:

• src/providers/types.ts — ProviderAdapter interface from spec/providers.schema.json
• src/mcp/tools/_generated.ts — Zod schemas and type exports from spec/mcp-tools.yaml

Run pnpm gen:schemas after modifying either spec file. CI enforces this with --check.

Adding a provider

Use the /add-provider skill in Claude Code, or follow src/providers/CLAUDE.md. Every adapter must satisfy ProviderAdapter in src/providers/types.ts — do not relax the schema to fit the adapter.

Adding an MCP tool

Use the /mcp-tool skill. The skill adds the tool to spec/mcp-tools.yaml, runs pnpm gen:schemas, creates the handler in src/mcp/tools/<toolset>/<name>.ts, and wires it into the registry. All four annotation hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) are required on every tool.

Conventional commits

feat(scope): description
fix(scope): description
docs / refactor / chore / test / perf / ci

Use pnpm changeset to record a release note before merging a feat or fix.

Milestones

Milestone	Status	What ships
M0 — Scaffold	✅	Tooling, CI, stubs, generated types
M1 — GCP MVP	✅	init / up / down / status / ssh / logs on GCP
M2 — Remote Mgmt	✅	tunnel, config, agents, gateway; SSH connection pool
M3 — AWS + Azure	✅	AWS EC2 + Azure VM adapters; stacks list
M4 — Local VM	✅	Local adapter (SSH bootstrap, no Pulumi); doctor
M5 — MCP Layer	✅	mcp serve (stdio), all CLI ops as MCP tools, progress tracking
M6 — Plan/Apply	✅	plan + apply; deploy-plan schema; MCP HTTP transport; workflow_deploy_app
M7 — v1.0 Polish	✅	Full doctor surface; destroy command; --dry-run across commands; CI guide

See docs/roadmap.md for the public roadmap and upcoming work.

License

MPL-2.0 — see LICENSE.