stroblme
07fa5a2dc2
Every output is a target and every input besides prompt a reading. A targets setting gives descriptions, values, ranges and per-target guards, model takes a trained pack's artifact digest, min_confidence defaults to the model's threshold. A command is applied whole or not at all, and targets the model was not trained on read degraded. The home path (area/kind ports, groups, brightness, temperature answers) is gone.
83 lines
3.8 KiB
Markdown
83 lines
3.8 KiB
Markdown
# Agents over MCP
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Fluksio exposes flow tools over MCP. An agent can inspect, edit, publish,
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and run flows with the permissions of the user who authorizes it.
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## Connect an agent
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Set `MCP_ENABLED=true` in the engine's environment and restart it, under
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`environment` in `compose.yml` for the Docker container. It defaults to off.
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Configure your MCP client with an HTTP endpoint:
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- Docker container: `http://localhost:8080/mcp`
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- Deployment: `https://<your-domain>/mcp`
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The endpoint has to be the address in `FRONTEND_HOST`, which is also the
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issuer of the client's tokens.
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The client registers, opens browser authorization, and receives an OAuth
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token after you approve access. The issuer and browser redirects use
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`FRONTEND_HOST` and `ENVIRONMENT`, so configure those for the addresses your
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client and browser can reach.
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Manage registered clients under **Admin → Agents**. Revoking a client
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invalidates its access. MCP uses a separate signing key at
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`OAUTH_PRIVATE_KEY_FILE`; rotating that key invalidates all MCP tokens.
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An instance connected to a [portal](../interface/portal.md) also answers
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through it, at `https://hub.fluksio.com/i/<instance-id>/mcp` (the portal's
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own `hub.` host for a custom one). The portal forwards the endpoint and its
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OAuth, and the instance checks the agent's token as it does locally. The
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consent page opens in the instance as the portal serves it, so open the
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instance from the portal first if this browser has not recently.
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## Available tools
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| Task | Tools |
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| Inspect flows | `list_flows`, `get_flow`, `get_node_source`, `list_node_types`, `get_graph`, `list_shared_nodes` |
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| Inspect values | `get_flow_state`, `get_message_history` |
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| Inspect the instance | `list_secrets` (names only), `get_modules`, `get_health`, `get_metrics`, `list_failures`, `list_runs` (live cascades) |
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| Inspect devices | `list_devices`, `get_device` |
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| Edit flows | `save_flow`, `save_node_source`, `validate_flow`, `publish_flow`, `discard_draft`, `delete_flow` |
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| Operate flows | `run_flow`, `trigger_node`, `start_flow`, `stop_flow`, `pause_flow`, `resume_flow`, `cancel_node` |
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| Install node packages | `apply_modules` |
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Tools call the same API as the browser. Drafts, validation, version checks,
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and superuser restrictions apply. Secrets cannot be read back.
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A useful workflow: ask the agent to inspect the flow, save a draft, and
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validate it. Review the draft before asking it to publish. The agent has
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a publish tool, so make your intent explicit.
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## The assistant
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A superuser configures an OpenAI-compatible provider under
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**Settings → Assistant**, with a base URL, API key, and model. This enables
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the dashboard's Assistant entry for signed-in users.
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The assistant uses the same tools with your own permissions. Draft edits
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appear in the editor. Each answer streams in as the model writes it and
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renders as markdown with a tool trace.
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Conversations are stored per user on the instance; the bin button clears
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yours.
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`MCP_ENABLED` is only needed for external clients, so the built-in assistant
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works without it.
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## Control
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A live [Wren](../reference/node-types.md#wren) or
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[Assistant](../reference/node-types.md#assistant) node with its `prompt` and a
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`reply` or `actions` wired adds a **Control** tab to the chat. Wren uses its
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local model, the Assistant node the provider above.
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Choose a conversation and type a command. It goes out on the node's prompt,
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which is where a `stt` node writes what a device heard, so typed and spoken
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commands are one conversation: the words heard so far, the command, each
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reply, and the reported actions with their target message, value and whether
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each was applied. A node whose prompt is another's `unhandled` answers in that
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node's conversation. Wren's `apply`, `min_confidence` and `targets` settings
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decide whether it writes to its targets. Control conversations stay in the
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browser and clear on reload.
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