Chat Reply

Send text back to the open chat turn — the explicit reply point. Put one on each branch of an If to answer differently; the first Chat Reply that runs wins. text supports {{ }} expressions; blank = read replyField (or auto-detect reply/text/message) from the input. Input passes through so the flow can keep going after replying.

Finding it in the library

Search the builder's node library for Chat Reply (it lives under Output). A single click opens the in-editor docs panel shown here — description, ports, and every property, without leaving the canvas. Double-click (or drag) to add it to the workflow.

Wired up in the builder

Chat Reply in a real, runnable flow — captured live from the Studio editor, exactly as it looks on your canvas. This is the same workflow used for the example input & output below.

How it’s configured

The node’s Configure panel as it opens in the builder when you select the step — every setting laid out with real values. Click any field to edit it.

Ports

Ports are the node’s contract with its neighbours. In the editor a port label renders bold when wired and italic when optional; ◈ ports accept attachment carriers rather than data wires.

How data flows through it

Chat Reply consumes the content of the incoming envelope — when it is fed directly by a trigger, the trigger’s wrapper is unwrapped at the node boundary so the node sees the actual data, not the metadata shell. Its output becomes the payload for the next node, while the envelope (trace ids, correlation, binary refs) rides along untouched. In the Runs view you always see the whole envelope for both sides of this node.

Expressions in the config

String-typed properties accept {{ }} expressions evaluated against the incoming item at run time — e.g. {{ $json.customer.email }}. On this node that’s text. JSON- and code-typed fields never interpolate — they are passed through literally.

Build it with AI

Every node in this reference is reachable through Flowdrome’s AI Copilot and the MCP tools — say what you want, and the graph surgery happens server-side. Node types resolve fuzzily, so the catalog label (Chat Reply) works as well as the exact type id (output.chat-reply).

In the Copilot panel (or any connected AI):

add a chat reply node after the trigger

As a step in a create_chain_workflow call:

{"type":"Chat Reply","config":{}}

curl -s -X POST http://localhost:48170/mcp -H "content-type: application/json" -d '{ "jsonrpc": "2.0", "id": "1", "method": "tools/call", "params": { "name": "add_node", "arguments": { "workflowId": "<id>", "type": "Chat Reply" } } }'

Example input & output

Captured from a real test run of the workflow above — this is what you see in the run data panel after pressing Test workflow.

Input — what the node received

Output — what the node produced

Property reference

Every setting, with its type and default — the same fields shown configured in the panel above.

Related nodes

The rest of the Output group — the same folder you’d scan in the editor’s library.

• HTTP Request Sends workflow data to an HTTP endpoint.
• Play Audio Plays binary audio (e.g
• Show Image Shows a binary image (e.g
• Send Message Sends a normalized message to Gmail, Slack, Telegram, Discord, or a generic webhook endpoint.
• Respond to Webhook Answers the HTTP trigger's request mid-flow with a status, headers, and body — the run continues afterwards
• Send Email Sends an email over SMTP (STARTTLS/TLS/none, AUTH PLAIN/LOGIN)
• Slack Sends a Slack message (text or Block Kit blocks) to a channel via chat.postMessage with a bot token
• Discord Sends a Discord message through a webhook or as a bot (token + channel)

This page is generated from the node registry by gen-node-docs.mjs on every site build — ports, properties, defaults and visibility rules cannot drift from the code. The screenshots and example data are captured from a live Flowdrome by npm run shots:nodes and npm run gen:examples.