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MongoDB and Slack integration

Save yourself the work of writing custom integrations for MongoDB and Slack and use n8n instead. Build adaptable and scalable Development, Data & Storage, Communication, and HITL workflows that work with your technology stack. All within a building experience you will love.

How to connect MongoDB and Slack

  • Step 1: Create a new workflow
  • Step 2: Add and configure nodes
  • Step 3: Connect
  • Step 4: Customize and extend your integration
  • Step 5: Test and activate your workflow

Step 1: Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

MongoDB and Slack integration: Create a new workflow and add the first step

Step 2: Add and configure MongoDB and Slack nodes

You can find MongoDB and Slack in the nodes panel. Drag them onto your workflow canvas, selecting their actions. Click each node, choose a credential, and authenticate to grant n8n access. Configure MongoDB and Slack nodes one by one: input data on the left, parameters in the middle, and output data on the right.

MongoDB and Slack integration: Add and configure MongoDB and Slack nodes

Step 3: Connect MongoDB and Slack

A connection establishes a link between MongoDB and Slack (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.

MongoDB and Slack integration: Connect MongoDB and Slack

Step 4: Customize and extend your MongoDB and Slack integration

Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect MongoDB and Slack with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

MongoDB and Slack integration: Customize and extend your MongoDB and Slack integration

Step 5: Test and activate your MongoDB and Slack workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from MongoDB to Slack or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.

MongoDB and Slack integration: Test and activate your MongoDB and Slack workflow

ETL pipeline for text processing

This workflow allows you to collect tweets, store them in MongoDB, analyse their sentiment, insert them into a Postgres database, and post positive tweets in a Slack channel.

Cron node: Schedule the workflow to run every day

Twitter node: Collect tweets

MongoDB node: Insert the collected tweets in MongoDB

Google Cloud Natural Language node: Analyse the sentiment of the collected tweets

Set node: Extract the sentiment score and magnitude

Postgres node: Insert the tweets and their sentiment score and magnitude in a Posgres database

IF node: Filter tweets with positive and negative sentiment scores

Slack node: Post tweets with a positive sentiment score in a Slack channel

NoOp node: Ignore tweets with a negative sentiment score

Nodes used in this workflow

Popular MongoDB and Slack workflows

Automated Upwork Job Alerts with MongoDB & Slack

Overview This automated workflow fetches Upwork job postings using Apify, removes duplicate job listings via MongoDB, and sends new job opportunities to Slack. Key Features: Automated job retrieval** from Upwork via Apify API Duplicate filtering** using MongoDB to store only unique jobs Slack notifications** for new job postings Runs every 20 minutes** during working hours (9 AM - 5 PM) This workflow requires an active Apify subscription to function, as it uses the Apify Upwork API to fetch job listings. Who is This For? This workflow is ideal for: Freelancers looking to track Upwork jobs in real time Recruiters automating job collection for analytics Developers who want to integrate Upwork job data into their applications What Problem Does This Solve? Manually checking Upwork for jobs is time-consuming and inefficient. This workflow: Automates job discovery based on your keywords Filters out duplicate listings, ensuring only new jobs are stored Notifies you on Slack when new jobs appear How the Workflow Works Schedule Trigger (Every 20 Minutes) Triggers the workflow at 20-minute intervals Ensures job searches are only executed during working hours (9 AM - 5 PM) Query Upwork for Jobs Uses Apify API to scrape Upwork job posts for specific keywords (e.g., "n8n", "Python") Find Existing Jobs in MongoDB Searches MongoDB to check if a job (based on title and budget) already exists Filter Out Duplicate Jobs The Merge Node compares Upwork jobs with MongoDB data The IF Node filters out jobs that are already stored in the database Save Only New Jobs in MongoDB The Insert Node adds only new job listings to the MongoDB collection Send a Slack Notification If a new job is found, a Slack message is sent with job details Setup Guide Required API Keys Upwork Scraper (Apify Token) – Get your token from Apify MongoDB Credentials – Set up MongoDB in n8n using your connection string Slack API Token – Connect Slack to n8n and set the channel ID (default: #general) Configuration Steps Modify search keywords in the 'Assign Parameters' node (startUrls) Adjust the Working Hours in the 'If Working Hours' node Set your Slack channel in the Slack node Ensure MongoDB is connected properly Adjust the 'If Working Hours' node to match your timezone and hours, or remove it altogether to receive notifications and updates constantly. How to Customize the Workflow Change keywords: update the startUrls in the 'Assign Parameters' node to track different job categories Change 'If Working Hours': Modify conditions in the IF Node to filter times based on your needs Modify Slack Notifications: Adjust the Slack message format to include additional job details Why Use This Workflow? Automated job tracking without manual searches Prevents duplicate entries in MongoDB Instant Slack notifications for new job opportunities Customizable – adapt the workflow to different job categories Next Steps Run the workflow and test with a small set of keywords Expand job categories for better coverage Enhance notifications by integrating Telegram, Email, or a dashboard This workflow ensures real-time job tracking, prevents duplicates, and keeps you updated effortlessly.

ETL pipeline for text processing

This workflow allows you to collect tweets, store them in MongoDB, analyse their sentiment, insert them into a Postgres database, and post positive tweets in a Slack channel. Cron node: Schedule the workflow to run every day Twitter node: Collect tweets MongoDB node: Insert the collected tweets in MongoDB Google Cloud Natural Language node: Analyse the sentiment of the collected tweets Set node: Extract the sentiment score and magnitude Postgres node: Insert the tweets and their sentiment score and magnitude in a Posgres database IF node: Filter tweets with positive and negative sentiment scores Slack node: Post tweets with a positive sentiment score in a Slack channel NoOp node: Ignore tweets with a negative sentiment score

Build your own MongoDB and Slack integration

Create custom MongoDB and Slack workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

MongoDB supported actions

Aggregate
Aggregate documents
Delete
Delete documents
Find
Find documents
Find And Replace
Find and replace documents
Find And Update
Find and update documents
Insert
Insert documents
Update
Update documents

Slack supported actions

Archive
Archives a conversation
Close
Closes a direct message or multi-person direct message
Create
Initiates a public or private channel-based conversation
Get
Get information about a channel
Get Many
Get many channels in a Slack team
History
Get a conversation's history of messages and events
Invite
Invite a user to a channel
Join
Joins an existing conversation
Kick
Removes a user from a channel
Leave
Leaves a conversation
Member
List members of a conversation
Open
Opens or resumes a direct message or multi-person direct message
Rename
Renames a conversation
Replies
Get a thread of messages posted to a channel
Set Purpose
Sets the purpose for a conversation
Set Topic
Sets the topic for a conversation
Unarchive
Unarchives a conversation
Get
Get Many
Get & filters team files
Upload
Create or upload an existing file
Delete
Get Permalink
Search
Send
Send and Wait for Response
Update
Add
Adds a reaction to a message
Get
Get the reactions of a message
Remove
Remove a reaction of a message
Add
Add a star to an item
Delete
Delete a star from an item
Get Many
Get many stars of autenticated user
Get
Get information about a user
Get Many
Get a list of many users
Get User's Profile
Get a user's profile
Get User's Status
Get online status of a user
Update User's Profile
Update a user's profile
Create
Disable
Enable
Get Many
Update

FAQs

  • Can MongoDB connect with Slack?

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  • Can I use Slack’s API with n8n?

  • Is n8n secure for integrating MongoDB and Slack?

  • How to get started with MongoDB and Slack integration in n8n.io?

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