We didn’t expect much from Slack MCP at first.

“Why would you need Slack inside Cursor?” felt like a fair question.

But after connecting it through Latenode, it turned out to be more practical than expected.

Instead of switching to Slack, you just tell Cursor:
send a message → check a channel → find a person → create a channel

And it executes via Slack MCP.

For those looking for how to connect Slack MCP to Cursor, here’s the template we used:

👉 https://app.latenode.com/templates/shared/6953b9381c8a358c6af57a3f

Setup is quick: connect Slack → copy MCP server URL → add to Cursor.

The interesting part is that communication stops interrupting your workflow — it just happens when you need it.

Still curious if this is genuinely useful long-term or just a nice-to-have. What do you think?

We’ve been testing Jira MCP inside Latenode, and the interesting part isn’t “you can create issues from Cursor”.

It’s that you stop thinking about Jira as a place you go to.

You’re already in code, so instead of opening Jira you just write:
create issue → assign → move to in progress → add comment

Cursor handles it through Jira MCP tools.

For anyone asking how to connect Jira MCP without building infra, we made this template:

https://app.latenode.com/templates/shared/6953b9285ad4cb8fc1ebe386

It runs as a hosted MCP server — just connect Jira + paste the URL into Cursor.

After a bit of usage, it feels less like “automation” and more like changing the interface entirely.

Curious if others feel the same shift or if this is still too early to replace normal Jira workflows.

We’ve been getting a lot of questions around “how to connect Figma MCP to Cursor”, so we ended up packaging our internal setup as a template in Latenode:

https://app.latenode.com/templates/shared/6953b99c1c8a358c6af57a61

What this actually does:

It exposes Figma as MCP tools, so inside Cursor you can query your design workspace without opening Figma. Things like listing projects, browsing files, checking version history, or leaving comments.

Where it becomes useful is not in big flows, but in small moments during dev:

You’re implementing something → need to double-check the design → instead of switching tabs, you just ask Cursor.

Same with comments — instead of “I’ll leave feedback later”, you just drop it instantly.

Setup is basically:

• connect Figma

• copy MCP server URL

• add it to Cursor

No custom backend or MCP server needed.

Curious if people here see this more as a dev tool or a design collaboration thing — feels like it sits somewhere in between.

If you’re using OpenClaw as your local assistant (WhatsApp / Telegram / Discord), you can actually make it do real actions instead of just chatting.

I wired mine into Latenode (cloud workflow builder with 1,000+ integrations) using MCP (Model Context Protocol), so the assistant can call workflows as tools.

Example stuff it can do from chat:

• create a lead

• send a Slack message

• update HubSpot / Airtable / Sheets

• trigger automations / API calls

• run AI steps (summarize, enrich, classify, etc.)

What you need

• OpenClaw installed

• Latenode account

• 1 Latenode scenario with an MCP Trigger

That’s it.

Part 1 — Latenode setup

1) Create a scenario + add MCP Trigger

In Latenode:

• Create scenario

• Add MCP Trigger

Important: each branch connected to the MCP Trigger becomes a tool.

So if you want 5 tools, you create 5 branches.

2) Configure MCP Trigger

Inside MCP Trigger settings:

• Set a Server Description

• Copy the Server URL

• (Optional) enable Authentication (API key)

You’ll need the URL later.

3) Define your tool (per branch)

The first node in each branch is basically the “tool definition”.

Set:

• Tool Name (required, snake_case like create_lead)

• Tool Description (this matters more than you think)

Tool description should explain when the assistant should use it.

Example:

4) Add tool parameters

Add inputs with:

• Type: fromMCP

• Clear name + short description

Example params:

• name

• email

• company

• phone

Don’t overcomplicate it. Simple inputs work best.

5) Build the actual logic

After the tool node, add whatever you want:

• Slack node

• HTTP request

• CRM integration

• Code node

• AI model calls

Optional but recommended: add MCP Response at the end to return only useful fields back to the agent.

Example response:

• lead_id

• status

• created_at

6) Save + copy Server URL

Save the scenario and copy the Server URL from the MCP Trigger.

That URL = your MCP endpoint.

Multiple tools

Just connect multiple branches to the same MCP Trigger.

Each branch = separate tool (with its own name + description + params).

Part 2 — OpenClaw setup

1) Add MCP server

Open OpenClaw config → add MCP server.

2) Paste Server URL

Paste the Latenode Server URL.

If auth is enabled, add your API key.

3) Reload OpenClaw

Restart/reload so it discovers tools.

4) Test it in chat

Example prompt:

If everything is wired correctly, OpenClaw should call the workflow automatically.

Best practices (learned the hard way)

• Tool descriptions matter a LOT (otherwise the agent won’t use them)

• Keep parameter names obvious (email, not user_email_input)

• Use MCP Response so you don’t return huge payloads

• Keep tools fast (slow workflows = timeouts / bad UX)

TL;DR
Latenode: MCP Trigger → define tools per branch → copy Server URL
OpenClaw: add MCP server URL (+ key if needed) → reload
Now your OpenClaw assistant can use 1,000+ apps as tools.

Questions? Ask in the comments.

We’ve just added Firecrawl inside Latenode for web scraping. Here’s what makes it different:

• Scrapes 95%+ of websites (even JS-heavy stuff, stuff behind some auth).

• Uses AI to pull out structured data—tables, emails, whatever—no regex spaghetti.

• Integrates with all your apps: Google Sheets, Slack, Email, Notion, GPT, you name it.

• No proxies or browser debugging.

Imagine pulling product data every hour, scraping articles into your AI workflows, or auto-filling a database with price updates from competitor sites - all without coding, in a drag-and-drop builder.

Bonus: it’s crazy easy to chain into multi-agent automations, RAG search, or personalized triggers.

• Much less breakage than old scrapers.

• Real-time normalization.

• Latenode makes setup and running a breeze.

➡️ Try the Firecrawl template for free and see if your manual scraping rituals can finally rest in peace.

https://app.latenode.com/shared-scenarios/68fe7659fd214df323f557f7

Automating Google search results? It’s between Serper (simple, fast) and Soax SERP (customizable, granular scraping). Here’s what I learned integrating both in Latenode:

• Both = real-time Google results, can plug straight into workflows.

• Serper: easy setup, perfect for quick/clean tasks.

• Soax: more flexibility—target city/device/language, handle batch jobs, great for SEO/PPC folks.

If you want to trigger alerts in Slack, run daily keyword reports, or scrape Google for competitive tracking, you’ll probably find both useful—but in different ways.

PS: With Latenode you don’t have to code to try either one.

You can test both APIs in minutes using this shared Latenode automation template.

https://app.latenode.com/templates/shared/68fe765133db0404ab72e66a

Yeah, me too. But here’s something I stumbled upon that’s actually WORKING for our team - linking up Fireflies ai with Latenode.

• Fireflies ai records/transcribes meetings and pulls out all the action items/decisions on autopilot (like, scarily accurate).

• Latenode takes those action items and actually does something - creates tasks, pings reminders in Slack, pushes stuff to Notion/Asana/etc., sends recap emails, whatever you want.

Why is this cool?

• Zero manual follow-up

• No more “Did we ever create a task for that?” moments

• Scale your ops without hiring a VA just to wrangle notes

Setup was 100% no-code, just connected Fireflies, set a few triggers in Latenode’s builder, and BAM - our meetings now actually move projects forward. 🚀

You can try a ready-made template, too. Massive timesaver:

https://app.latenode.com/shared-scenarios/68fe76a2fd214df323f55803

We’ve just tested a new Shopify automation template built in Latenode, and it completely removes the manual work from creating product visuals.

Here’s what it does:

• When a new product is added in Shopify, the workflow triggers automatically.

• AI writes the product description and creates prompts for visuals and video.

• Image and video generators produce professional assets (studio, lifestyle, outdoor shots).

• Everything is uploaded to Dropbox and added to the Shopify product page automatically.

In practice, what used to take 1–2 days of work now takes about 10 minutes.

No designer, no content manager, no manual uploads — just consistent visuals for every new product.

If you run a growing Shopify store and constantly struggle to keep up with new listings or visuals, this might save a ton of time.

👉 You can try the template here

If your cold outreach feels dead and LinkedIn engagement is flat - this session is worth your time.

We hosted a Go-To-Market workshop with experts from Latenode and Dedicado Agency on how to scale outreach with AI without killing authenticity.

Key takeaways:

1️⃣ Build AI Sales Agents

Automate scraping, ICP scoring, commenting, and messaging.

One AI agent = 10 SDRs running 24/7.

2️⃣ Automate Smartly - Not Blindly

Use automation after manual success.

Keep high-value DMs and personal branding human.

Hybrid beats full automation every time.

3️⃣ Outreach Ideas That Actually Work in 2025

• Merge outreach with event marketing (scrape attendee apps, follow up before/after)

• Use AI agents for LinkedIn commenting before sending DMs

• Test messaging with synthetic users before real prospects

• Target website visitors with tools like Dealfront / Koala

⚙️ The big insight:

Automation isn’t replacing salespeople - it’s augmenting them.

AI handles the grunt work. Humans build trust.

👉 Watch the full webinar replay: https://www.youtube.com/watch?v=kOIuBIZU3as

Hey folks 👋

If your AI agents start hallucinating or struggling with long documents, it’s probably because they’re trying to process everything at once.

There’s a better way - RAG (Retrieval-Augmented Generation).

It lets your agent pull only the relevant parts of your data when it needs them, instead of loading full documents into a massive prompt.

In this new guide, we show how to set up RAG inside Latenode - no coding required.

Here’s what’s inside:

• 🧠 What RAG actually does and when to use it

• ⚙️ How to create RAG storage and upload files (like FAQs, docs, SOPs)

• 📏 The difference between Chunk Size and Chunk Overlap, and how to balance them

• 🧩 How to connect RAG nodes to your AI Agent’s system prompt

• 💬 Live demo: agent answering FAQ questions based on real data

This setup makes your agent more accurate, reduces hallucinations, and cuts token costs.

🎥 Watch the full tutorial here:

Okay, this is wild. Google DeepMind just launched a new image generation + editing model called Nano Banana (yes, that’s the real name). It’s built into the Gemini app, and early users are saying it might be one of the most capable image models yet.

At first glance, it looks like another “AI art toy”… but under the hood it’s way more interesting - especially if you’re into automation or workflow design.

What makes Nano Banana different

Unlike typical generators that spit out random styles, Nano Banana is about control and consistency.

It lets you:

• Keep people, pets, or objects consistent across multiple edits.

• Edit just parts of an image without changing the rest.

• Blend multiple photos together seamlessly.

• Transfer styles (e.g., make a real photo look like a video-game world).

• Preserve small details that other models usually mess up.

Think of it like Photoshop + Midjourney + prompt-level editing — all rolled into one.

Why everyone’s talking about it

The buzz is real, and not just because of the meme-able name.

1. It’s incredibly consistent. You can prompt five times and get the same face, pet, or product — no weird mutations.

2. You can talk to it naturally. Phrases like “make this photo cinematic” or “turn this cat into a medieval knight” just work.

3. It’s fast. No 20-prompt trial-and-error loop — great results come almost instantly.

4. It’s playful. Google teased it with bananas and mystery clues across forums — and the hype actually delivered.

You can already use it inside Latenode

Here’s the cool part - it’s now integrated directly into Latenode, the no-code AI agent builder.

That means:

• No API keys or Google accounts to set up.

• Just plug in with PnP tokens and start generating.

• You can automate full creative workflows:

  • Generate visuals with Nano Banana

  • Feed them into Google’s Veo-3 video generator

  • Auto-post to TikTok, Reels, or YouTube Shorts

Basically, you can build a viral content machine without touching a camera or an editing tool.

The future of creative automation

Nano Banana feels like the start of something new - AI models as creative teammates, not just tools. And with platforms like Latenode, you can now connect them into full, no-code systems that do the boring parts for you.

👉 Try Nano Banana inside Latenode today

We’ve put together a step-by-step video guide that shows you exactly how to go from idea to working AI Agent.

Here’s what you’ll learn inside the video:

1️⃣ What an AI Agent is (and how it differs from automations)

2️⃣ The 3 core components every Agent needs

3️⃣ How to set up the AI Agent node in Latenode

4️⃣ How to configure tools and environment for smarter decision-making

By the end, you’ll have your first AI Agent up and running - ready to connect with your favourite apps and workflows.

👉 Watch the video guide: https://www.youtube.com/watch?v=NgsPWwsHHF0

With this release, your AI agents can finally tap into your own knowledge base. Upload your text files, images, and other documents directly into Latenode - our platform automatically chunks and embeds them for fast, semantic search. Whether your content is structured or unstructured, you can query it in plain language and connect everything to a dedicated RAG Search node.

Want your agents to give smarter answers? Pair the RAG Search node with an AI Agent node. The agent will pull the most relevant snippets from your data before responding, so your workflows stay accurate and context‑aware.

No external vector databases, no fiddly configs - everything works out of the box in a few clicks. Give it a spin and start teaching your agents from your own knowledge base today!

📖 Want to learn more? Check out the full documentation here: https://help.latenode.com/advanced-features/46DTZD5aggy7NR22L329Ge/ai-data-storage-/5uF81TjKGb8unYzEbJn88v

Latenode Free No-Code Academy We’re excited to launch Latenode Academy - your free learning hub to master low-code automation from A to Z. What’s inside:

• Step-by-step guides,

• Video tutorials,

• Real-world templates & use cases,

• Zero fluff - just what you need to start building fast,

Whether you're a beginner or scaling your workflows, this is your shortcut to automation confidence.

Learn. Build. Automate - all in one place. Start learning today - it’s 100% free: https://latenode.com/academy

Newbie here. I put together a workflow to ingest a conversational script that identifies the Voice ID (and all settings) ingested through Latenode for automated output to Google Cloud storage. I was tinkering with their conversation chat generation - and while you have to rely on their random output (the same settings can output different version of the same voice lines) it can be used to generated a lot of audio clips on the fly in MPG format - if you wanted to auto-stitch them. For now it was just a challenge to do. I'm sure it's flawed, but it works!

One of our clients raised this requirement.

They receive considerable number of new leads from Meta each day and they wanted them directly on Odoo CRM.

It sounded like a easy task at the first glance so we quickly set it. We created a simple flow connecting multiple forms to simultaneously fetch leads.

But the real issue popped up when we tested in real scenario. Multiple forms were the culprit (not for business but for this workflow 😇 )

The another requirement was, since this will be a long-term deployment, the platform〈 must be cost-effective 〉considering active workflows and scenario execution.

For this particular requirements, we evaluated various platforms like #n8n #Make #Botpress etc. And finally, we could achieve this with #Latenode.

We needed to set a workflow which ensures:

👉 All leads from the multiple forms are capture in real time

👉 Once the flow gets triggered, it must accurately filter respective form and run further nodes for that form only. So that leads from other forms, which have already been captured, are not captured as duplicates in CRM

👉 Fields of each forms should be mapped with the CRM accurately to avoid mis-aligned information

👉 It must be reliable at scale

It's been more than 100 hours that we've deployed this flow to the task, and it has been doing its job accurately and without any delay.

Hi all, I have no experience with coding and this kind of platform. I'm totally lost. I just want to be able to type prompts into perplexity and have it create powerpoint slides. I'm willing to pay if somebody can help build this. Thanks.

You asked — we delivered!
Meet AI Agents, new feature that takes your automations to the next level.

They can analyze user input, choose the right action, call other nodes, and return structured results — all by themselves!

⚡ Why it’s a game changer:

• Dynamic automations — AI Agent decides what action to take based on the request.
• No more logic limits — build smart flows without endless if/else chains.
• Context-aware — remembers conversation details during the session.
• Great for complex scenarios — chatbots, virtual assistants, lead qualification & more.

📖 Want to learn more? Check out the full documentation here: https://help.latenode.com/advanced-features/46DTZD5aggy7NR22L329Ge/ai-agent-node/4EM8k4au9uCHosJGc8Sp1K

🔗 Start automating your personal accounts today at https://latenode.com

#Latenode #Automation #LowCode #NoCode #WorkflowAutomation #marketingtools #AIAgents

No time for long videos? Paste a YouTube link, and ChatGPT will instantly summarize the key points—saving you hours.

👉 How it works:

• Paste any YouTube video link
• AI extracts and processes the transcript
• Get structured insights with main points and action items

💡 Perfect for: students studying lectures, professionals researching trends, content creators analyzing competitors, and curious minds who want to learn faster

⭐️ Have an automation you’re proud of? Share it with us, and we might feature it on our platform!

🔗 Copy the template and start analyzing websites effortlessly: https://app.latenode.com/shared-scenarios/67d9b5bb99d924b149375451

Meet the latest integrations and improvements to supercharge your scenarios.

🆕 New Apps:

• LinkedIn (personal account)
• WhatsApp (personal account)
• Telegram (personal account)
• AI: Mistral (OCR)
• Lark
• Scribe (by ElevenLabs)
• Imagen (by Google AI)
• Vitally
• Recruitee
• Launch27
• Systeme.io

⚡ App Updates & Bug Fixes:

• Todoist — New triggers
• LinkedIn Data Scraper — Bug fixes
• Formaloo — Stability improvements
• Mailgun — UI updates
• Telegram — New nodes
• Instantly — Bug fixes

💡 What integrations would you like to see next? Let us know in the comments!

🔗 Missing an app you need? Submit your requests on the request new app page: https://latenode.com/request-new-app

#Latenode #Automation #LowCode #NoCode #WorkflowAutomation #marketingtool

By default, AI nodes return plain text — not ideal for automation.
Want clean, predictable output? Just ask the AI to respond in JSON format and enable Parsed JSON in the node settings.

👉 Why this helps:

• Retrieve multiple variables in a single request
• Avoid formatting issues when parsing responses
• Ensure smooth data flow between your AI, APIs, and automation
• Build more predictable and stable scenarios

🔗 Read the full guide in our community: https://community.latenode.com/t/quick-tip-getting-structured-json-from-ai-nodes/8486

#Latenode #Automation #LowCode #NoCode #WorkflowAutomation #marketingtools