How do I import "Travel AssistantAgent" into n8n?

Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.

Which integrations does "Travel AssistantAgent" use?

It uses: chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader. The flow diagram above shows how each service connects across the 14 nodes. Filter OpenRuna by integration to find related workflows and tools.

Can I import a sanitized export without credentials?

Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own chat and memoryMongoDbChat credentials in n8n after import.

What trigger type does "Travel AssistantAgent" use?

Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.

Is "Travel AssistantAgent" free to use?

OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader.

← Workflows

Travel AssistantAgent

14 nodes · chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent

Engine: n8n
Nodes: 14
Trigger: scheduled/triggered
Source file: 2039_Stickynote_Webhook_Automation_Webhook.json

Workflow flow

IntegrationsChatMemoryMongoDbChatLmChatGoogleGeminiVectorStoreMongoDBAtlasEmbeddingsOpenAiAgentWebhookDocumentDefaultDataLoaderTextSplitterRecursiveCharacterTextSplitter@n8n/n8n-nodes-langchain.chat@n8n/n8n-nodes-langchain.memoryMongoDbChat@n8n/n8n-nodes-langchain.lmChatGoogleGemini+5 more

100%

TRIGGER

When chat message received

@n8n/n8n-nodes-langchain.chat

MongoDB Chat Memory

@n8n/n8n-nodes-langchain.memoryMongoDbChat

Google Gemini Chat Model

@n8n/n8n-nodes-langchain.lmChatGoogleGemini

MongoDB Atlas Vector Store

@n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas

Embeddings OpenAI

@n8n/n8n-nodes-langchain.embeddingsOpenAi

TRIGGER

Webhook

Default Data Loader

@n8n/n8n-nodes-langchain.documentDefaultDataLoader

Recursive Character Text Splitter

@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter

Embeddings OpenAI1

@n8n/n8n-nodes-langchain.embeddingsOpenAi

AI Traveling Planner Agent

@n8n/n8n-nodes-langchain.agent

MongoDB Atlas Vector Store1

@n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas

11 steps · flows top to bottom, branches left to right

Browse by integration

chat memoryMongoDbChat lmChatGoogleGemini vectorStoreMongoDBAtlas embeddingsOpenAi agent webhook documentDefaultDataLoader textSplitterRecursiveCharacterTextSplitter

Browse all integrations →

Download n8n JSON Download sanitized JSON Download flow graph

Import into n8n

Download the n8n JSON file (full or sanitized).
In n8n: Workflows → Import from file.
Open each node and reconnect credentials to your accounts.
Test with manual execution before enabling triggers.

Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.

View source corpus ↗

Overview

Travel AssistantAgent (14-node n8n automation, chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader) is free on OpenRuna — view the graph and export the JSON to import into n8n.

What this workflow does

Built in n8n, "Travel AssistantAgent" chains 14 nodes to move data between chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader. 14 nodes · chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent A scheduled/triggered entry point kicks it off, and each node passes data to the next until the run completes. OpenRuna renders the node graph and offers the JSON export so you can import and adapt it in minutes. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

Study how data moves from chat to memoryMongoDbChat before building your own variant.
Share it with your team as a documented reference for scheduled/triggered automations in the chat stack.
Import "Travel AssistantAgent" into n8n, reconnect credentials for chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader, and run the same automation in your own workspace.
Use it as a starting template when wiring chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader — adjust node parameters to your accounts and record IDs.

Example output

Imported into n8n, "Travel AssistantAgent" exposes 14 configured nodes. Trigger type: scheduled/triggered. Integrations: chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader. Set your credentials on the chat node, then verify each downstream node picks them up. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Ask Claude to turn the "Travel AssistantAgent" JSON into a plain-English runbook, node by node. It can flag where chat rate limits or missing retries might bite before you go live.

ChatGPT

Drop the workflow JSON or this OpenRuna page URL into ChatGPT and ask for a step-by-step runbook: triggers, branches, and which fields to customise for chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader. Handy for onboarding teammates new to n8n.

Cursor

In Cursor, ask Agent mode to parameterise "Travel AssistantAgent" — extract chat IDs and secrets into environment variables without changing the 14-node structure.

Frequently asked questions

How do I import "Travel AssistantAgent" into n8n?: Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
Which integrations does "Travel AssistantAgent" use?: It uses: chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader. The flow diagram above shows how each service connects across the 14 nodes. Filter OpenRuna by integration to find related workflows and tools.
Can I import a sanitized export without credentials?: Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own chat and memoryMongoDbChat credentials in n8n after import.
What trigger type does "Travel AssistantAgent" use?: Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
Is "Travel AssistantAgent" free to use?: OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for chat, memoryMongoDbChat, lmChatGoogleGemini, vectorStoreMongoDBAtlas, embeddingsOpenAi, agent, webhook, documentDefaultDataLoader.