Ready-to-Use n8n Workflow Templates
Browse 307+ free automation templates. Import directly into your n8n instance.
Auto-create TikTok videos with VEED.io AI avatars, ElevenLabs & GPT-4
Automate the creation and distribution of trending TikTok videos using AI avatars. This workflow connects Telegram, Perplexity, OpenAI, ElevenLabs, VEED.io, and BLOTATO to generate scripts, synthesize voice, create video, and publish across multiple social platforms. Content creators and marketers can rapidly produce engaging short-form video content without manual editing.
Create childrens AI story videos from drawings and auto-publish to YouTube with Blotato
💥 From Drawing to Story: Auto-Publish AI Video to YouTube with Blotato Overview Transform a hand-drawn character sketch into a fully animated, narrated video story — automatically. This 3-part pipeline uses Claude AI, image generation, and video synthesis to go from a simple drawing to a publish-ready video, with no manual editing required. Perfect for: indie creators, educators, storytellers, and anyone who wants to bring hand-drawn characters to life at scale. How It Works Part 1 — From Drawing to Story: Bringing Characters to Life A form submission triggers the workflow with an uploaded drawing The image is analyzed by Claude AI to extract characters and traits Character images are generated via Nano Banana (image generation API) A full story is written by Claude AI, split into scenes, and passed to Part 2 Part 2 — From Characters to Scenes: Rendering the Visual Story Character images are downloaded and converted to Base64 references Scene images are generated using Nano Banana with character consistency Scene image URLs are mapped and the video pipeline is triggered Part 3 — From Scenes to Screen: Video, Narration & Final Render Video prompts and narration context are generated by Claude AI Videos are generated via AtlasCloud (Kling Pro 3.0) with polling loop Narration audio is created with ElevenLabs and uploaded Shotstack assembles the final video with audio sync Final video is published to YouTube (and optionally TikTok) > ⚠️ Important — Workflow Structure > > This template is split into 3 separate workflows. > Each part must be imported and deployed in its own workflow in n8n. > > 📺 Watch the step-by-step tutorial to set everything up correctly: > > @youtube Requirements Credentials needed Blotato API credentials (YouTube/TikTok publishing) AtlasCloud API (Kling Pro 3.0 video generation) Anthropic API key (Claude AI for story & prompts) ElevenLabs API key (narration audio) Shotstack API key (video assembly) Nano Banana API key (image generation) Setup steps Configure credentials for each service above in n8n Set up a form trigger with a file upload field for the drawing Deploy the 3 workflows in order and connect them via webhooks Run a test submission with a simple sketch to validate the full pipeline 🎥 Watch This Tutorial 👋 Need help or want to customize this? 📩 Contact: LinkedIn 📺 YouTube: @DRFIRASS 🚀 Workshops: Mes Ateliers n8n Need help customizing? Contact me for consulting and support : Linkedin / Youtube / 🚀 Mes Ateliers n8n
Use skills In n8n agent node
This template gives you a framework to use skills in any n8n agent. You can use this as a starting point and add any other tools or patterns needed for your use case. What are “skills”? Skills are a context management standard created by Anthropic for use in Claude code. Basically, instead of having a HUGE system prompt, skills split that into lots of small, structured instruction files that tell an agent how to do a specific kind of task. Instead of stuffing a massive prompt full of rules, the agent: finds the relevant skill file reads it and follows the steps inside It’s a simple pattern that makes managing system prompts for general purpose agents much more straightforward. See an example of a skills repo here. What this workflow does Responds to messages in n8n Chat (or Chat Hub) Builds an “available skills” index from one or more GitHub repos Lets the agent browse folders + fetch skill files (Markdown) as needed Uses the skill content to guide how it completes tasks How it (roughly) works A chat message comes in. The workflow lists directories in the configured skills repos (root + if present), filters out noise, and merges everything into one directory map. That directory map gets injected into the agent’s system prompt so it knows what skill files exist. When it needs instructions, it uses tools: List Files by Path Name to explore folders * Get a File From GitHub to pull the skill file as raw text (no base64) Same “skills” pattern as the CLI tools The flow is: find a skill → open it → follow the steps, the same way it works in the CLI tools, but running inside n8n, so you don’t need to download or install anything locally. How to set it up (Required) Add your GitHub credentials to each node that needs it (Required) Add your OpenRouter credentials to the chat node or replace with the provider of your choosing (Optional) Add more repos to (any skills GitHub repo works as long as your credentials have access to it, such as any public repo) (Optional) Add more tools and turn it into whatever agent you actually need
Scrape, search and browse the web with a Firecrawl AI agent webhook
Turn any prompt into structured web data. Send a POST request with a natural language prompt and an optional JSON schema, and get back clean, structured results scraped from the web by an AI agent powered by Firecrawl. Use Cases Data Enrichment: Feed company names or URLs from your CRM and get back structured firmographic data (industry, funding, team size, tech stack). Lead Generation: Ask the agent to find pricing, contact pages, or product details for a list of competitors. Market Research: Extract structured pricing plans, feature comparisons, or product catalogs from any website. Content Aggregation: Pull structured news, events, or job postings from across the web on a schedule. Sales Intelligence: Enrich prospect lists with company info, recent news, or tech stack details before outreach. How It Works Receive Scrape Request receives a POST request with and an optional . Validate Output Schema checks the schema. If none is provided, it falls back to a permissive default. If the schema is malformed, it returns a clear error via Return Schema Error. Research & Extract Web Data takes the prompt and uses the full Firecrawl toolkit to research the web: - Search (): Finds relevant pages and sources across the web. - Scrape (): Extracts clean, structured content from any URL. - Interact (interactContext, interact, interactStop): Lets the agent interact with scraped pages in a live session. After scraping a page, the agent can click buttons, fill forms, navigate dynamic content, and extract data that static scraping cannot reach, all without managing sessions manually. This combination gives the AI agent complete web navigation capabilities. It can discover sources, read pages, and interact with dynamic content autonomously. Format Response to Schema (Structured Output Parser) formats the agent's response to match the provided (or default) schema. Return Structured Results sends the structured JSON back to the caller. Setup Requirements Firecrawl API Key: Sign up at firecrawl.dev and grab your API key. Connect it in the Firecrawl credential nodes. LLM Provider: Configure your Primary Chat Model and Fallback Chat Model nodes (e.g., OpenRouter, OpenAI, Anthropic). The template uses two model nodes for reliability, plus a separate Parser Chat Model for the output parser. n8n Instance: Self-hosted or cloud. Make sure the webhook node is set to accept POST requests. API Reference Endpoint Request Body | Field | Type | Required | Description | |-------|------|----------|-------------| | | string | Yes | Natural language instruction for the agent | | | object | No | JSON Schema defining the desired output structure | Response Returns a JSON object matching the provided schema, or a flexible object if no schema was given. Testing Examples Basic Request (No Schema) The agent decides the output structure on its own. Expected output: A JSON object with whatever structure the agent finds most appropriate for the data. Since no schema was provided, the internal default () is used. Request With a Custom Schema You define exactly the shape of data you want back. Expected output: Invalid Schema (String Instead of Object) Expected output: Invalid Schema (Array Instead of Object) Expected output: Same error response as above. Invalid Schema (Missing Property) Expected output: Same error response as above. Invalid Schema (Invalid Value) Expected output: Same error response as above. Workflow Architecture Schema Validation Logic The Validate Output Schema node runs this validation before passing data to the agent: If is missing or null, the default permissive schema is used: . If is present, it must be a JSON object (not a string, array, or primitive). It must have a property with a valid value: , , , , or . If validation fails, the workflow returns an error response with a helpful message and example schema. Notes The Format Response to Schema node (Structured Output Parser) requires the schema to be passed as a JSON string. The expression handles this conversion. The agent has access to Firecrawl's full toolkit: search, scrape, and interact. With all three connected, the agent has complete web navigation powers. It can discover sources via search, extract content via scrape, and interact with dynamic JavaScript-heavy pages via interact. The interact tools let the agent scrape a page first and then continue working with it in a live session, clicking buttons, filling forms, and navigating deeper, all without manual session management. The agent autonomously decides which tools to use based on the prompt. Response times vary depending on the complexity of the prompt and how many pages the agent needs to visit. Simple lookups take a few seconds; deep research can take longer.
Generate AI videos with Google Veo3, save to Google Drive and upload to YouTube
Automate the creation of AI-generated videos using Google Veo3, then save them to Google Drive and publish them on YouTube. This workflow connects Google Sheets for data input, Google Veo3 via HTTP requests for video generation, Google Drive for storage, and YouTube for publishing, with OpenAI generating video titles.
Generate & auto-post AI videos to social media with Veo3 and Blotato
Automate the entire process of generating AI videos and posting them across multiple social media platforms. This workflow connects Google Sheets, Veo3, Blotato, and various social media APIs to create, upload, and publish video content. Content creators and marketers can effortlessly produce and distribute daily video updates, product showcases, or educational snippets.
Send AI job application auto-replies with Gmail, OpenAI GPT-4o and SMTP
Automate sending personalized AI-generated auto-replies to job applications received via Gmail. Gmail data triggers an OpenAI GPT-4o agent to craft a structured email, which is then sent via SMTP. Recruiters or hiring managers can use this to acknowledge applications, provide status updates, or request additional information efficiently. This saves significant time and effort in managing applicant communications.
Generate AI viral videos with Seedance and upload to TikTok, YouTube & Instagram
Automate the creation of AI-generated viral videos and their multi-platform distribution. This workflow connects AI tools like Seedance, Fal AI, and OpenAI with Google Sheets, HTTP requests, and Blotato for content generation, storage, and social media uploads. It's ideal for content creators, marketers, and businesses looking to rapidly produce and disseminate engaging video content across TikTok, YouTube, and Instagram.
OpenClaw Clone 🦞: Expandable Personal Telegram AI Agent Template
Create your own expandable personal AI agent within Telegram, powered by OpenClaw. This workflow connects Telegram for message input, OpenAI for transcription and AI processing, Google Gemini for advanced chat, and FTP for image handling, all while utilizing Postgres for chat memory.
Personal life manager with Telegram, Google services & voice-enabled AI
Manage your personal life using voice or text commands through Telegram. This workflow connects Telegram, Google Calendar, Gmail, Google Tasks, and an AI assistant powered by OpenRouter to process requests. It's ideal for busy individuals who want to quickly schedule events, send emails, or manage tasks on the go. This automation streamlines daily organization, saving significant time and mental effort.
Generate AI viral videos with NanoBanana & VEO3, shared on socials via Blotato
Automate the creation and distribution of viral AI-generated videos across multiple social media platforms. This workflow uses Telegram to receive video ideas, AI agents to generate scripts, NanoBanana to create images, and VEO3 to generate videos, which are then uploaded and shared via Blotato to YouTube, TikTok, LinkedIn, Facebook, Instagram, Threads, Bluesky, Pinterest, and Twitter (X), with status updates in Google Sheets.
Build an AI confidence coach for women with GPT-4o, Google Sheets and Gmail
Builds an AI confidence coach for women, providing personalized coaching and weekly check-ins. It connects Google Sheets for user data and conversation logs, Gmail for email communication, and OpenAI for AI coaching responses, triggered by chat interactions or a weekly schedule. This workflow empowers coaches or community managers to offer scalable, personalized support, fostering confidence and growth among their users.
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