app/docs/code/agents.md

Agents over MCP

Fluksio exposes flow tools over MCP. An agent can inspect, edit, publish, and run flows with the permissions of the user who authorizes it.

Connect an agent

Set MCP_ENABLED=true in the engine's environment and restart it, under environment in compose.yml for the Docker container. It defaults to off.

Configure your MCP client with an HTTP endpoint:

• Docker container: http://localhost:8080/mcp
• Deployment: https://<your-domain>/mcp

The endpoint has to be the address in FRONTEND_HOST, which is also the issuer of the client's tokens.

The client registers, opens browser authorization, and receives an OAuth token after you approve access. The issuer and browser redirects use FRONTEND_HOST and ENVIRONMENT, so configure those for the addresses your client and browser can reach.

Manage registered clients under Admin → Agents. Revoking a client invalidates its access. MCP uses a separate signing key at OAUTH_PRIVATE_KEY_FILE; rotating that key invalidates all MCP tokens.

An instance connected to a portal also answers through the portal's API address, for example https://portal.example.com/i/<instance-id>/mcp. The portal forwards MCP and OAuth requests; the instance checks the agent's token as it does locally. Open the instance from the portal first so the browser can show its consent page.

Available tools

Task	Tools
Inspect flows	list_flows, get_flow, get_node_source, list_node_types, get_graph, list_shared_nodes
Inspect values	get_flow_state, get_message_history
Inspect the instance	list_secrets (names only), get_modules, get_health, get_metrics, list_failures, list_runs (live cascades)
Inspect devices	list_devices, get_device
Edit flows	save_flow, save_node_source, validate_flow, publish_flow, discard_draft, delete_flow
Operate flows	run_flow, trigger_node, start_flow, stop_flow, pause_flow, resume_flow, cancel_node
Install node packages	apply_modules

Tools call the same API as the browser. Drafts, validation, version checks, and superuser restrictions apply. Secrets cannot be read back.

A useful workflow: ask the agent to inspect the flow, save a draft, and validate it. Review the draft before asking it to publish. The agent has a publish tool, so make your intent explicit.

The assistant

A superuser configures an OpenAI-compatible provider under Settings → Assistant, with a base URL, API key, and model. This enables the dashboard's Assistant entry for signed-in users.

The assistant uses the same tools with your own permissions. Draft edits appear in the editor. Each answer streams in as the model writes it and renders as markdown with a tool trace. Conversations are stored per user on the instance; the bin button clears yours. MCP_ENABLED is only needed for external clients, so the built-in assistant works without it.

In both tabs, chips above the input offer quick prompts: the messages you send most often in this browser, then a few starters. A tap puts the text in the input to edit and send. Double-clicking, or double-tapping, one of your own messages does the same.

Control

A live Wren or Assistant node with its prompt and a reply or actions wired adds a Control tab to the chat. Wren uses its local model, the Assistant node the provider above.

Choose a conversation and type a command. It goes out on the node's prompt, which is where a stt node writes what a device heard, so typed and spoken commands are one conversation: the words heard so far, the command, each reply, and the reported actions with their target message, value and whether each was applied. A node whose prompt is another's unhandled answers in that node's conversation. Wren's apply, min_confidence and targets settings decide whether it writes to its targets. Control conversations stay in the browser and clear on reload.