Microsoft Outlook AI Email Assistant
28 nodes · manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule
- Engine
- n8n
- Nodes
- 28
- Trigger
- scheduled/triggered
- Source file
- 1551_Mondaycom_Schedule_Send_Scheduled.json
Workflow flow
When clicking ‘Test workflow’
Manual
OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured
Check Mail Schedule Trigger
Schedule
Update Contacts Schedule Trigger
Schedule
Microsoft Outlook23
MicrosoftOutlook
Monday.com - Get Contacts
MondayCom
Rules
Airtable
Categories
Airtable
Delete Rules
Airtable
Airtable - Contacts
Airtable
Convert to Markdown
Markdown
Email Messages
Set
Merge
Merge
Set Importance
MicrosoftOutlook
AI: Analyse Email
@n8n/n8n-nodes-langchain.agent
Set Category
MicrosoftOutlook
Loop Over Items
SplitInBatches
If
IF
Contact
Airtable
20 steps · flows top to bottom, branches left to right
Browse by integration
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.
Overview
Microsoft Outlook AI Email Assistant is a free n8n workflow on OpenRuna — 28 nodes connecting manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule, mondayCom, airtable. Download the JSON, view the flow diagram, and import it into your n8n instance.
What this workflow does
"Microsoft Outlook AI Email Assistant" is an n8n automation built from 28 nodes spanning manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule, mondayCom, airtable. 28 nodes · manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule It starts from a scheduled/triggered trigger and routes data through every node in order. 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
- Use it as a starting template when wiring manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule, mondayCom, airtable — adjust node parameters to your accounts and record IDs.
- Import "Microsoft Outlook AI Email Assistant" into n8n, reconnect credentials for manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule, mondayCom, airtable, and run the same automation in your own workspace.
- Share it with your team as a documented reference for scheduled/triggered automations in the manual stack.
- Study how data moves from manual to microsoftOutlook before building your own variant.
Example output
Imported into n8n, "Microsoft Outlook AI Email Assistant" exposes 28 configured nodes. Trigger type: scheduled/triggered. Integrations: manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule, mondayCom, airtable. Reconnect the manual credential first, then walk the remaining nodes top to bottom. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.
Tips by platform
Claude
Paste the exported JSON for "Microsoft Outlook AI Email Assistant" into Claude and ask it to explain each of the 28 nodes. Claude is good at suggesting credential mappings for manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule, mondayCom, airtable, plus error-handling and idempotency improvements before you run it in production.
ChatGPT
Have ChatGPT generate a checklist for adapting "Microsoft Outlook AI Email Assistant" to your accounts — which manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule, mondayCom, airtable credentials to create and which node parameters to change first.
Cursor
Open the downloaded JSON in Cursor and use Agent mode to refactor hard-coded URLs into env vars, or to generate tests for any Code nodes. Keep the OpenRuna flow diagram open so you do not break connection order across the 28 nodes.
Frequently asked questions
- How do I import "Microsoft Outlook AI Email Assistant" 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 "Microsoft Outlook AI Email Assistant" use?
- It uses: manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule, mondayCom, airtable. The flow diagram above shows how each service connects across the 28 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 manual and microsoftOutlook credentials in n8n after import.
- What trigger type does "Microsoft Outlook AI Email Assistant" 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 "Microsoft Outlook AI Email Assistant" 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 manual, microsoftOutlook, lmChatOpenAi, outputParserStructured, agent, schedule, mondayCom, airtable.
Related resources
- Agent
PraisonAI
24/7 AI employee team for automating complex challenges. Low-code multi-agent framework with handoffs, guardrails, memory, RAG, and 100+ LLM providers
- Agent
Prompt Optimizer
AI prompt optimization tool with multi-round iterative improvements, dual-mode optimization for system and user prompts, and multi-model support. Available as web app, desktop app, Chrome extension, and Docker deployment. AGPL-3.0 licensed
- Agent
Archon
Workflow engine for deterministic AI coding agents. Define development processes as YAML workflows (planning → implementation → validation → review → PR) with isolated Git worktrees for parallel execution. MIT licensed
- Agent
A2A Protocol
Agent2Agent (A2A) open protocol enabling communication and interoperability between opaque agentic applications. Donated to Linux Foundation by Google with 50+ technology partners. Apache 2.0 licensed
- Agent
CAMEL
First and best multi-agent framework for building scalable agent systems. Apache 2.0 licensed with extensive tooling for agent communication and task automation
- Agent
Neuron AI
PHP Agentic Framework for building production-ready AI driven applications. Connect components (LLMs, vector DBs, memory) to agents that can interact with your data. MIT licensed
- Agent
smolagents
Lightweight agent framework centered on tool use and code-executing workflows
- Agent
Supermemory
Memory API and app for AI agents that provides fast, scalable, context-aware storage and retrieval across projects. MIT licensed
