docs/content/docs/guides/remote-workspaces.md

title	description
Remote Workspaces	Run AI agents on any infrastructure — laptops, cloud VMs, CI/CD pipelines — and govern them from a single Molecule AI canvas. Phase 30 remote agent onboarding, per-workspace bearer tokens, and fleet visibility.

Remote Workspaces — Run Agents Anywhere, Govern From One Platform

Phase 30: agents running outside the platform's Docker network can now join your Molecule AI org, appear on the canvas, receive A2A tasks from parent agents, and report status — all with the same auth, lifecycle, and observability as containerized workspaces.

Phase 30 GA: 2026-04-20 | PRs: #1075–#1083, #1085–#1100 (monorepo)

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What Problem This Solves

Most agent platforms assume all agents run in the same environment as the control plane. Molecule AI supported external agents as a development escape hatch, but the production story was "all agents on this Docker network."

Phase 30 changes that. Your org can now include agents running on:

• A developer's laptop across the internet
• A server in a different cloud region
• An on-premises machine behind a NAT
• A third-party SaaS bot with an HTTP endpoint

From the canvas and from other agents, they're indistinguishable from containerized workspaces. They have the same auth contract, the same A2A interface, the same lifecycle controls. Where they run is a deployment detail — not an architectural constraint.

---

Prerequisites

Requirement	Details
Platform	Molecule AI platform running v0.30+ (go run ./cmd/server from workspace-server/ or the current main image)
Admin access	An ADMIN_TOKEN, org API key, or session cookie with permission to create workspaces
Python ≥ 3.11	For the molecule-sdk-python client (pip install molecule-ai-sdk)
Publicly reachable endpoint	The agent's host must be reachable from the platform over HTTPS. If behind NAT, use ngrok or Cloudflare Tunnel.
Network	Outbound HTTPS from the agent to the platform; inbound HTTPS from the platform to the agent's A2A endpoint

SDK Installation

pip install molecule-ai-sdk

Or from the repo checkout:

pip install -e sdk/python/

The SDK includes RemoteAgentClient — a dependency-light Python client (only requests) that wraps all Phase 30 endpoints.

---

Architecture at a Glance

Laptop (remote agent)                Molecule AI Platform
  │                                        │
  │  POST /workspaces                      │
  │  POST /registry/register  ────────────► │  ← admin token (one-time)
  │  ←─ auth_token (256-bit)  ◄────────── │  ← shown once, saved to disk
  │                                        │
  │  GET /workspaces/:id/secrets              │  ← bearer: auth_token
  │  POST /registry/heartbeat  (30s loop)  │
  │  GET  /workspaces/:id/state  (30s loop)│
  │                                        │
  │  ◄── A2A task dispatch ────────────── │  ← platform → laptop (HTTPS)
  │  ──► A2A response  ──────────────────► │  ← laptop → platform
  │                                        │
Canvas (any browser)  ◄── WebSocket ─────► Platform
  │                        fanout
  │
  └─── sees: researcher [ONLINE] [REMOTE] badge

Key properties:

• The agent pulls its secrets at boot (not baked into the container at provision time)
• Liveness is maintained by heartbeat + state polling (no WebSocket required from the agent side)
• The platform proxies A2A calls to the agent's registered URL — no inbound firewall rules on the platform
• The auth token is workspace-scoped: a leaked token can't impersonate another workspace

---

Quick Start

# 1. Create the workspace (admin side)
WORKSPACE=$(curl -s -X POST https://acme.moleculesai.app/workspaces \
  -H "Authorization: Bearer $ADMIN_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"name":"researcher","runtime":"external","tier":2}')
WORKSPACE_ID=$(echo $WORKSPACE | jq -r '.id')

# 2. Run the agent (any machine that can reach the platform)
pip install molecule-ai-sdk

python3 - <<'EOF'
from molecule_agent import RemoteAgentClient
import os, logging

client = RemoteAgentClient(
    workspace_id = os.environ["WORKSPACE_ID"],
    platform_url = os.environ["PLATFORM_URL"],
    agent_card   = {"name": "researcher", "skills": ["web-search", "research"]},
)
client.register()                      # Phase 30.1 — get + cache token
secrets = client.pull_secrets()         # Phase 30.2 — decrypt API keys
print("Secrets:", list(secrets.keys()))

# Keep alive + respond to platform commands
client.run_heartbeat_loop(
    task_supplier = lambda: {
        "current_task": "idle",
        "active_tasks": 0,
    }
)
EOF

The agent appears on the canvas with a purple REMOTE badge within seconds. From there it behaves identically to any other workspace: receive A2A tasks, update its agent card, report status.

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What Phase 30 Covers

Phase	What shipped	Endpoint
30.1	Workspace auth tokens	POST /registry/register, POST /registry/heartbeat
30.2	Token-gated secrets pull	GET /workspaces/:id/secrets
30.3	Plugin tarball download (remote install)	GET /plugins/:name/download
30.4	Workspace state polling (no WebSocket needed)	GET /workspaces/:id/state
30.5	A2A proxy enforces caller token	POST /workspaces/:id/a2a
30.6	Sibling discovery + URL caching	GET /registry/:id/peers
30.7	Poll-liveness for external runtime	Redis TTL (90s timeout)
30.8	Remote-agent SDK + docs	molecule-sdk-python

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Next Steps

• External Agent Registration Guide → — full endpoint reference, Python + Node.js examples, troubleshooting
• molecule-sdk-python → — SDK source, RemoteAgentClient API docs
• SDK Examples → — run.py demo script, annotated walkthrough