stroblme
f569f325a7
The connector now serves /mcp, its OAuth documents and /hooks/ besides /api/v1/, refuses any dot segment (httpx resolves them, which carried /api/v1/../../mcp onto the MCP mount), addresses calls to the hub's host, and bridges served sockets by calling the app with a websocket scope. A hook without a secret answers the tunnel with the 404 (or 1008) of a wrong secret. Requests through the hub get the hub's issuer, resource and consent page in the OAuth metadata and the 401, and the MCP host check admits the hub while enrolled.
72 lines
3.3 KiB
Markdown
72 lines
3.3 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. The Python
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package defaults to off; the Docker template enables it.
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Configure your MCP client with an HTTP endpoint:
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- Local Docker stack: `http://api.localhost/mcp`
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- Deployment: `https://api.<your-domain>/mcp`
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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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`DOMAIN`, `ENVIRONMENT`, and `FRONTEND_HOST`, so configure those for the
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addresses your 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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| 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, and each answer includes a tool trace. Conversations
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are stored per user on the instance; the bin button clears 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 node](../reference/node-types.md#wren) with both `prompt` and
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`actions` wired adds a **Control** tab to the chat. It uses the node's local
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model and needs no assistant provider.
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Choose a node, type a command, and inspect the reported actions: target
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message, value, confidence, and whether each action was applied.
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The node's `apply` and `min_confidence` settings decide whether it writes
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to devices. Control conversations stay in the browser and clear on reload.
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