octopus-agentos
One-click remote dev/ops platform — browser VS Code + 5 AI CLIs + Octopus Blackboard, as an AWS/Azure Marketplace image.
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octopus-agentos — one-click remote dev-and-ops platform (Cloud Marketplace image)
From a single Packer source, build an AWS / Azure Marketplace-compliant image off Ubuntu LTS. Once deployed it's a browser VS Code + five AI CLIs remote dev-and-ops box with zero setup barrier. Positioning: docs/product-positioning.md.
Part of Octopus Core — the distribution form of the open infrastructure stack for governed AI. The Community edition brings all eight open Octopus modules into the image (the open ecosystem environment) — Evidence · Observe · Experience · Runtime · Replay · Inspect · Scout · Blackboard — and you wire/integrate them yourself.
Editions: Community vs Commercial
The driver is operational trust and accountability, not a regulatory mandate: the more autonomous your agents get, the more your team needs to prove — to itself, its customers, and its board — what the agents did and why, with or without a law. We treat ISO/IEC 42001 (voluntary, international, procurement-driven) as the international anchor; the EU AI Act / NIST AI RMF only as "if you sell into those markets, this aligns too."
Principle: we do not lock features, we sell operations. The core capability is fully open; organisations pay to run, manage, and be supported at organisational scale. This is classic open-core (in the tradition of GitLab / Grafana).
| Community | Commercial | |
|---|---|---|
| In one line | Everything required to build and run a governed AI system yourself. | Everything required to operate governed AI systems across an organisation. |
| License | Apache-2.0 | Commercial |
| Form | This repo's AgentOS self-host image + the open Octopus Core packages, in your VPC | Multi-tenancy, SSO/RBAC, enterprise policy center, centralized Evidence Vault, audit retention, compliance reporting, enterprise dashboard, SaaS/hosted, SLA, commercial support |
| You pay for | Nothing (cloud compute only) | Operations at org scale, and support |
Nothing a self-hoster needs to build, run, govern, and prove an AI system sits behind the commercial line. See docs/EDITIONS.md · the engineering seam map docs/OPEN-CORE-SEAMS.md · the commercial spec (planned) docs/COMMERCIAL.md.
Platform capabilities
- All eight open Octopus modules in the image (Apache-2.0, the open ecosystem
environment — the Community edition brings them in; you integrate them yourself,
they are not auto-wired):
octopus-evidence·octopus-observe·octopus-experience(binoctomem, plusoctopus-experience-mcp) ·octopus-runtime·octopus-replay·octopus-inspect·octopus-scout(plusoctopus-scout-mcp) ·octopus-blackboard(binsoctoboard/blackboard/octopus-blackboard-mcp, wired to the CLIs by step 14). Manifest:config/octopus-modules.env - Five AI CLIs:
claude·codex·gemini·grok·cursor-agent(on the global PATH) - Shared blackboard: Octopus Blackboard as the multi-agent coordination layer — all five CLIs join one board over MCP out of the box: who's changing what, and every decision / risk / handoff, tamper-evident and replayable
- Browser VS Code: code-server + preinstalled AI extensions + one-click tasks to launch each CLI and the board
- Keyless AI on AWS Bedrock: attach an IAM role and call Bedrock with the instance identity
(one-switch
octopus-setup bedrock onfor Claude Code + a genericbedrockCLI); data never leaves your AWS account - Secrets via the customer's KMS:
octopus-secretspluggable backends (secretsmanager/ssm/kms-file/env); plaintext lives only in an in-memory tmpfs, never on disk; cost and backend are the customer's choice (see docs/security.md) - Cost-aware hardening: UFW allows only 22/443 by default, Caddy security headers, SSH hardening; heavier items via
octopus-hardenon demand - One-click ready: Caddy automatic HTTPS + a random password generated on first boot;
octopus-setupinjects API keys - Zero-barrier ops: docker/kubectl/git/psql preinstalled, passwordless sudo, direct reach inside your VPC's private network
- Compliance: the image contains no secrets; keys are injected after deployment
Layout
packer/ aws.pkr.hcl / azure.pkr.hcl / variables.pkr.hcl (with file uploads of config/)
scripts/ 00-base → 10-install(release+EULA) → 11-ai-clis → 12-vscode-server → 13-platform
→ 14-blackboard → 14b-octopus-modules → 15-bedrock → 16-secrets → 17-security
→ 20-cloud-init → 30-harden → 90-cleanup/deprovision
config/ ai-clis.env · octopus-modules.env · vscode/ · code-server.yaml · caddy/ · systemd/ · bin/ · profile.d/
test/ image self-check (during build, FAIL aborts) · smoke-test.sh (post-deploy)
docs/ positioning · requirements matrix · test runbook · both marketplace listing guides
Quick start
brew install packer # or see the HashiCorp install docs
make init # install packer plugins
make fmt # validate templates
make check # release gate: source preflight + Packer validate + shellcheck
# Configure each cloud's credentials (AWS: env vars / profile; Azure: az login)
make aws OS_VERSION=octopus-agentos-1.0.0
make azure OS_VERSION=octopus-agentos-1.0.0 AZ_SUBSCRIPTION_ID=...
Path to listing
- Run
make checkto verify package/script sources, Packer templates, and shell scripts. - Pin / verify the module and CLI package versions in
config/octopus-modules.envandconfig/ai-clis.envwhen you need a reproducible marketplace build; leave*_VERempty to track latest. - Build with
make aws/make azure— the built-in self-check catches common rejection reasons. - Submit per
docs/aws-listing-guide.md/docs/azure-listing-guide.md.
Compliance details: docs/requirements-matrix.md.
Release readiness
- Source preflight for the five AI CLIs, two installer URLs, Blackboard, and the seven other
open Octopus modules (
make preflight) -
Bring the open Octopus modules into the image— done: all eight Apache-2.0 modules are installed (blackboard in step 14, the other seven in step 14b); the Community edition is the open ecosystem environment and you integrate them yourself (not auto-wired) - Integrate Octopus Blackboard (shared board + MCP config for the five CLIs)
- EULA / bundled-license docs (
docs/EULA.txt,docs/LICENSES.txt) - Draft listing copy and marketplace guides (
docs/listing-content.md,docs/aws-listing-guide.md,docs/azure-listing-guide.md) - Marketplace media assets: final logo and screenshots
- Each cloud's build credentials (AWS profile /
az login) - First real-hardware build verification: after
make aws, launch an instance and run through "open browser → enter password → use a CLI"; seedocs/testing-runbook.md
Collected info
- ★ 3 stars
- Language: Shell
- Source updated: 8/25/2026
Config for your environment
Replace {MCP_ENDPOINT_URL} with this MCP’s endpoint URL (from its repo or docs above). No API key — you connect directly.
Tool
OS
Config file: ~/.cursor/mcp.json
{
"mcpServers": {
"mcp-server": {
"url": "{MCP_ENDPOINT_URL}"
}
}
}Paste into mcpServers in the config file. Restart Cursor after saving.
If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.