{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-enescingoz--awesome-n8n-templates","slug":"enescingoz--awesome-n8n-templates","name":"awesome-n8n-templates","type":"workflow","url":"https://n8n.partnerlinks.io/h1pwwf5m4toe","page_url":"https://unfragile.ai/enescingoz--awesome-n8n-templates","categories":["automation","rag-knowledge","documentation"],"tags":["ai-agents","ai-automation","automation","automation-templates","awesome","awesome-list","integration","low-code","n8n","n8n-automation","n8n-template","no-code-ai","no-code-automation","self-hosted","telegram-bot","workflow-automation"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-enescingoz--awesome-n8n-templates__cap_0","uri":"capability://automation.workflow.pre.built.workflow.template.library.with.ai.first.patterns","name":"pre-built workflow template library with ai-first patterns","description":"Provides 280+ JSON workflow files organized into 15+ platform-specific categories (Gmail, Telegram, Slack, Discord, Notion, Airtable, etc.) with ~80% featuring integrated AI processing through OpenAI, Google Gemini, MistralAI, and LangChain. Templates are structured as importable n8n workflow definitions with standardized metadata (title, description, department, link) enabling one-click deployment into self-hosted or cloud n8n instances without manual configuration.","intents":["I need to quickly spin up an email automation workflow with AI content generation without building from scratch","I want to see production-ready patterns for RAG implementations, memory management, and multi-modal AI processing","I'm looking for reference implementations of Telegram bots, Discord integrations, or Slack workflows with AI capabilities","I need to understand how to wire together multiple services (Gmail + OpenAI + Notion) in a single workflow"],"best_for":["solo developers and small teams building automation workflows without deep n8n expertise","non-technical founders prototyping AI-powered automation MVPs","DevOps engineers seeking CI/CD and workflow validation patterns","teams migrating from Zapier or Make to self-hosted n8n infrastructure"],"limitations":["Templates are JSON-based and require n8n instance to import; no visual drag-and-drop preview before import","API credentials and service-specific configuration must be manually added post-import; templates don't auto-detect available credentials","No built-in versioning or update mechanism; templates are static snapshots that may become stale as service APIs evolve","Limited to n8n's node ecosystem; workflows cannot use external Python/Node.js libraries without custom code nodes","No dependency resolution; complex workflows with 10+ integrations require manual troubleshooting if a single service API changes"],"requires":["n8n instance (self-hosted or cloud) with admin access to import workflows","API keys for target services (OpenAI, Google, Slack, Discord, etc.) depending on template","Basic understanding of n8n workflow structure and node configuration","Network connectivity to external services (Gmail, Telegram, Notion, etc.)"],"input_types":["JSON workflow definition files","API credentials (OAuth tokens, API keys)","Trigger data (email messages, Telegram updates, form submissions)"],"output_types":["Automated actions (emails sent, messages posted, documents created)","Structured data (JSON responses, database records, spreadsheet updates)","AI-generated content (text completions, classifications, summaries)"],"categories":["automation-workflow","tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_1","uri":"capability://memory.knowledge.rag.implementation.templates.with.vector.embedding.patterns","name":"rag implementation templates with vector embedding patterns","description":"Provides ~40 specialized templates demonstrating Retrieval-Augmented Generation workflows using LangChain, vector databases (Pinecone, Weaviate, Supabase), and embedding services (OpenAI, MistralAI). Templates show how to chunk documents, generate embeddings, store in vector indices, and retrieve relevant context for LLM prompts — enabling semantic search and knowledge-grounded AI responses without fine-tuning.","intents":["I want to build a chatbot that answers questions grounded in my company's documentation or knowledge base","I need to implement semantic search over large document collections without traditional keyword indexing","I'm building a customer support agent that retrieves relevant help articles before generating responses","I want to see how to integrate vector databases (Pinecone, Weaviate) with n8n and OpenAI for RAG workflows"],"best_for":["teams building knowledge-grounded chatbots or Q&A systems","enterprises with large document repositories needing semantic search","developers implementing RAG for the first time and needing reference patterns","product teams adding AI-powered search to existing applications"],"limitations":["Vector database setup and embedding generation incur per-token costs; templates don't include cost optimization strategies","Chunking strategies (fixed-size, semantic, recursive) are hardcoded in templates; no dynamic adjustment based on document type","No built-in reranking or relevance filtering; all retrieved chunks are passed to LLM, potentially increasing token usage","Templates assume synchronous retrieval; no support for async batch embedding or incremental index updates","Limited to single-vector-database patterns; no multi-index or hybrid search (vector + keyword) examples"],"requires":["Vector database account (Pinecone, Weaviate, Supabase, or self-hosted Milvus)","Embedding API key (OpenAI, MistralAI, or local embedding model)","LLM API key (OpenAI, Google Gemini, or MistralAI)","Document source (PDF, text files, web pages, or database records)","n8n instance with HTTP request and code node capabilities"],"input_types":["Documents (PDF, Markdown, plain text, web pages)","User queries (text strings)","Embedding vectors (pre-computed or generated on-the-fly)"],"output_types":["Retrieved document chunks (text with metadata)","LLM-generated responses grounded in retrieved context","Relevance scores or similarity metrics"],"categories":["memory-knowledge","automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_10","uri":"capability://automation.workflow.social.media.automation.with.content.scheduling.and.ai.generation","name":"social media automation with content scheduling and ai generation","description":"Provides templates for automating social media workflows: scheduling posts to Twitter/X, LinkedIn, Instagram, Facebook; generating AI-powered captions and hashtags; monitoring mentions and engagement; and routing social media interactions to support systems. Workflows use n8n's social media nodes, OpenAI/Gemini for content generation, and conditional logic for audience-specific posting.","intents":["I want to schedule social media posts across multiple platforms from a single workflow","I need to generate AI-powered captions and hashtags for social media content","I want to monitor social media mentions and route urgent messages to support teams","I need to automate social media engagement (likes, replies) based on keywords or sentiment"],"best_for":["marketing teams automating social media posting and scheduling","content creators generating captions and hashtags at scale","social media managers monitoring mentions and engagement","brands automating customer support on social platforms"],"limitations":["Social media API rate limits vary by platform; templates may require backoff logic for high-volume posting","Generated captions may require human review for brand consistency and tone","Engagement automation (likes, replies) may violate platform terms of service; templates should include compliance checks","Media uploads are limited; templates primarily handle text posts","Cross-platform scheduling requires separate API calls; no unified scheduling interface"],"requires":["Social media platform API credentials (Twitter/X, LinkedIn, Instagram, Facebook)","OpenAI or Google Gemini API key for content generation","n8n instance with social media nodes configured","Optional: image generation API for visual content"],"input_types":["Post content (text, images, links)","Scheduling metadata (platform, time, audience)","Social media mentions and engagement data"],"output_types":["Scheduled posts (across platforms)","Generated captions and hashtags","Routed social media interactions (to support systems)"],"categories":["automation-workflow","text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_11","uri":"capability://automation.workflow.database.integration.with.crud.operations.and.data.transformation","name":"database integration with crud operations and data transformation","description":"Provides ~20 templates for automating database workflows: creating/reading/updating/deleting records, syncing data between databases, transforming data formats, and querying for reporting. Workflows support multiple database types (PostgreSQL, MySQL, MongoDB, Supabase) via n8n's database nodes, include data validation and error handling, and demonstrate ETL patterns for data migration and synchronization.","intents":["I want to sync data between my database and external systems (CRM, Airtable, Sheets)","I need to automatically create database records from form submissions or API webhooks","I want to transform and clean data during database operations","I need to query databases and generate reports or exports"],"best_for":["developers automating database operations without writing SQL","teams syncing data between multiple databases or systems","businesses automating data entry and ETL workflows","organizations building database-driven automation workflows"],"limitations":["Database connection pooling is limited; high-concurrency workflows may exhaust connections","Complex SQL queries are not supported; templates use n8n's query builder which has limited expressiveness","Transaction support is limited; multi-step operations lack ACID guarantees","Large result sets may timeout; templates assume moderate data volumes","Schema changes require manual workflow updates; no automatic schema detection"],"requires":["Database instance (PostgreSQL, MySQL, MongoDB, Supabase, etc.)","Database credentials (host, port, username, password, database name)","n8n instance with database node configured for target database type","Optional: database migration tools for schema setup"],"input_types":["Database records (via query)","External data (form submissions, API responses, file uploads)","Transformation rules (for data mapping)"],"output_types":["Created/updated/deleted database records","Query results (JSON, CSV)","Synced data to external systems"],"categories":["automation-workflow","data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_12","uri":"capability://automation.workflow.wordpress.integration.with.content.automation.and.publishing","name":"wordpress integration with content automation and publishing","description":"Provides templates for automating WordPress workflows: creating/updating posts and pages, publishing content on schedule, syncing content from external sources (Notion, Sheets, CMS), and managing WordPress metadata (categories, tags, featured images). Workflows use n8n's WordPress node (REST API), handle content formatting and media uploads, and include conditional logic for content approval and scheduling.","intents":["I want to automatically publish blog posts from Notion or Google Sheets to WordPress","I need to schedule WordPress posts and manage publication workflows","I want to sync content between WordPress and other systems (CMS, knowledge base)","I need to automate WordPress metadata management (categories, tags, featured images)"],"best_for":["content teams automating blog publishing workflows","organizations syncing content across multiple platforms","publishers automating content scheduling and distribution","teams building WordPress-based content automation"],"limitations":["WordPress REST API requires authentication; templates must handle token expiration and refresh","Media uploads are limited; large files may timeout","Custom post types and fields require additional configuration; templates assume standard posts/pages","Content formatting may require manual adjustment; HTML/Markdown conversion is imperfect","WordPress plugins may conflict with API operations; templates assume standard WordPress installation"],"requires":["WordPress site with REST API enabled","WordPress application password or OAuth token","n8n instance with WordPress node configured","Optional: content source (Notion, Sheets, external CMS)"],"input_types":["Post content (text, HTML, Markdown)","Media files (images for featured images)","Metadata (categories, tags, publish date)"],"output_types":["Created/updated WordPress posts and pages","Published content (scheduled or immediate)","Synced content from external sources"],"categories":["automation-workflow","content-management-generation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_13","uri":"capability://text.generation.language.openai.and.llm.integration.with.multi.model.support.and.prompt.engineering","name":"openai and llm integration with multi-model support and prompt engineering","description":"Provides ~150 templates demonstrating OpenAI API integration (GPT-4, GPT-3.5, embeddings), prompt engineering patterns (few-shot learning, chain-of-thought, role-based prompting), and multi-model support (Google Gemini, MistralAI, DeepSeek). Templates show how to structure prompts, handle token limits, implement cost optimization, and chain multiple LLM calls for complex reasoning tasks.","intents":["I want to integrate OpenAI API into my n8n workflows for text generation and analysis","I need to implement prompt engineering patterns (few-shot, chain-of-thought) for better LLM outputs","I want to use multiple LLM providers (OpenAI, Gemini, MistralAI) and switch between them","I need to optimize LLM costs by implementing token counting and caching strategies"],"best_for":["developers building LLM-powered automation workflows","teams implementing prompt engineering at scale","organizations evaluating multiple LLM providers","builders optimizing LLM costs and performance"],"limitations":["Token counting is approximate; actual token usage may vary by model and encoding","Prompt engineering is empirical; templates provide patterns but require tuning for specific use cases","LLM outputs are non-deterministic; templates lack explicit quality assurance or validation","Cost optimization requires manual configuration; templates don't auto-select cheapest provider","Context window limits mean long conversations eventually exceed token budgets; no automatic context compression"],"requires":["OpenAI API key (or alternative LLM provider key)","n8n instance with HTTP request or native LLM nodes","Understanding of prompt engineering principles","Optional: token counting library for cost estimation"],"input_types":["Prompts (text instructions for LLM)","Context data (for few-shot learning or RAG)","User input (for conversational workflows)"],"output_types":["LLM-generated text (completions, classifications, summaries)","Embeddings (for semantic search or clustering)","Structured data (JSON extracted from LLM outputs)"],"categories":["text-generation-language","automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_14","uri":"capability://automation.workflow.workflow.validation.and.ci.cd.integration.for.automation.testing","name":"workflow validation and ci/cd integration for automation testing","description":"Provides templates and patterns for validating n8n workflows: unit testing workflow components, integration testing with mock services, validating workflow structure and node configuration, and implementing CI/CD pipelines for workflow deployment. Includes examples of error handling, logging, and monitoring patterns for production-ready workflows.","intents":["I want to test my n8n workflows before deploying to production","I need to validate workflow structure and catch configuration errors early","I want to implement CI/CD pipelines for automated workflow deployment","I need to add logging and monitoring to my workflows for debugging and observability"],"best_for":["teams deploying n8n workflows to production","organizations implementing workflow governance and quality assurance","DevOps teams automating workflow deployment and testing","developers building complex, multi-step automation workflows"],"limitations":["n8n lacks native unit testing framework; templates use workarounds with mock nodes","Integration testing requires external services or mocks; templates don't provide comprehensive test fixtures","CI/CD integration is manual; no native GitHub Actions or GitLab CI templates","Workflow versioning is limited; templates don't demonstrate version control best practices","Error handling is workflow-specific; no standardized error handling patterns across templates"],"requires":["n8n instance with admin access for testing","Optional: CI/CD platform (GitHub Actions, GitLab CI, Jenkins)","Optional: mock service framework (e.g., Mockoon, Wiremock)","Understanding of workflow testing and validation concepts"],"input_types":["Workflow definitions (JSON)","Test data (for unit/integration testing)","Configuration (for CI/CD pipelines)"],"output_types":["Test results (pass/fail, coverage metrics)","Deployment logs and status","Workflow validation reports"],"categories":["automation-workflow","safety-moderation","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_15","uri":"capability://text.generation.language.multi.provider.llm.orchestration.with.fallback.and.cost.optimization","name":"multi-provider llm orchestration with fallback and cost optimization","description":"Provides templates demonstrating how to orchestrate multiple LLM providers (OpenAI, Google Gemini, MistralAI, Anthropic, Ollama) with automatic fallback on failure, cost-aware provider selection, and unified prompt/response handling. Workflows implement provider abstraction layers, token counting for cost estimation, and dynamic provider switching based on model capabilities or pricing.","intents":["I want to use multiple LLM providers and automatically fallback if one fails","I need to select the cheapest LLM provider for each request based on token count","I want to compare outputs from different LLM providers for quality assurance","I need to implement LLM provider abstraction to avoid vendor lock-in"],"best_for":["teams building LLM-powered applications with high availability requirements","cost-conscious organizations optimizing LLM spending","developers evaluating multiple LLM providers","enterprises avoiding vendor lock-in with single LLM provider"],"limitations":["Provider abstraction adds complexity; templates require careful error handling and fallback logic","Cost estimation is approximate; actual costs depend on model-specific pricing and token encoding","Response format varies by provider; templates must normalize outputs for consistent handling","Fallback logic may increase latency; sequential provider attempts add request time","Provider availability varies; templates don't account for regional outages or rate limiting"],"requires":["API keys for multiple LLM providers (OpenAI, Gemini, MistralAI, Anthropic, etc.)","n8n instance with HTTP request and code node capabilities","Token counting library for cost estimation","Understanding of different LLM provider APIs and response formats"],"input_types":["Prompts (text instructions for LLM)","Provider preferences (cost, latency, quality)","Fallback configuration (provider order, retry logic)"],"output_types":["LLM-generated text (from selected provider)","Cost estimates and actual costs","Provider selection metadata (which provider was used, why)"],"categories":["text-generation-language","tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_2","uri":"capability://planning.reasoning.conversational.ai.agent.templates.with.memory.and.tool.integration","name":"conversational ai agent templates with memory and tool integration","description":"Provides templates implementing multi-turn conversational agents using LangChain memory management (conversation history, summarization), tool/function calling (API integrations, database queries), and reasoning chains. Workflows demonstrate how to maintain context across conversation turns, dynamically select tools based on user intent, and chain multiple API calls for complex tasks — enabling stateful chatbots and autonomous agents.","intents":["I want to build a chatbot that remembers conversation history and adapts responses based on prior context","I need an agent that can autonomously decide which tools to use (email, Slack, database) based on user requests","I'm implementing a customer support agent that can look up account info, create tickets, and send notifications in one workflow","I want to see how to implement chain-of-thought reasoning and multi-step task decomposition in n8n"],"best_for":["teams building stateful chatbots or virtual assistants","customer support teams automating multi-step resolution workflows","developers implementing autonomous agents with tool-use capabilities","enterprises needing conversational interfaces to internal systems (CRM, ticketing, databases)"],"limitations":["Memory management is in-process; no distributed session storage for multi-instance deployments","Conversation history grows unbounded; templates lack automatic summarization or pruning strategies","Tool selection relies on LLM reasoning; no explicit validation that selected tools match user intent, risking incorrect API calls","No built-in error recovery; if a tool call fails, workflows don't automatically retry or suggest alternatives","Context window limits mean long conversations eventually exceed token budgets; no automatic context compression"],"requires":["LLM API key (OpenAI, Google Gemini, MistralAI, or Anthropic)","LangChain integration (via n8n LangChain node or custom HTTP calls)","Tool/API credentials for services the agent will call (Slack, Gmail, database, etc.)","n8n instance with code node and HTTP request capabilities","Understanding of function calling/tool use schema (OpenAI format or equivalent)"],"input_types":["User messages (text)","Conversation history (array of message objects)","Tool definitions (schema describing available functions)"],"output_types":["Agent responses (text)","Tool calls with parameters (JSON)","Updated conversation history with memory state"],"categories":["planning-reasoning","tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_3","uri":"capability://automation.workflow.email.automation.with.ai.content.generation.and.classification","name":"email automation with ai content generation and classification","description":"Provides ~10 Gmail/email automation templates that trigger on incoming emails, extract content, classify using AI (spam detection, sentiment analysis, intent classification), generate AI-powered responses, and route to appropriate handlers. Workflows use OpenAI/Gemini for content analysis and generation, n8n's Gmail node for IMAP/SMTP operations, and conditional routing based on classification results.","intents":["I want to automatically classify incoming support emails by urgency and route to appropriate teams","I need to generate professional email responses using AI while maintaining brand voice","I want to filter spam and phishing emails using AI-powered classification before they reach users","I need to extract structured data (customer name, issue type, account number) from unstructured emails"],"best_for":["customer support teams automating email triage and response","sales teams qualifying leads from inbound emails","security teams detecting phishing and malicious emails","enterprises automating email-to-ticket or email-to-CRM workflows"],"limitations":["Gmail API rate limits (500 requests/100 seconds) can bottleneck high-volume email processing","AI classification is probabilistic; templates lack explicit confidence thresholds or fallback handling for ambiguous classifications","Generated email responses may require human review for compliance/legal reasons; no built-in approval workflow","Attachments are not processed; templates handle text-only email bodies","No support for email threading or conversation context; each email is processed independently"],"requires":["Gmail account with API access enabled and OAuth credentials","OpenAI or Google Gemini API key for content generation/classification","n8n instance with Gmail node configured","Destination service credentials (Slack, Airtable, ticketing system) for routing classified emails"],"input_types":["Email messages (from Gmail IMAP/API)","Email metadata (sender, subject, timestamp)","Email body (text content, may include HTML)"],"output_types":["Classification labels (priority, category, intent)","Generated email responses (text)","Routed messages to downstream systems (Slack channels, ticket queues, CRM records)"],"categories":["automation-workflow","text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_4","uri":"capability://automation.workflow.telegram.bot.templates.with.conversational.ai.and.command.handling","name":"telegram bot templates with conversational ai and command handling","description":"Provides ~18 Telegram bot templates demonstrating webhook-based message handling, command parsing (/start, /help, custom commands), integration with OpenAI/Gemini for conversational responses, and state management for multi-turn conversations. Workflows use n8n's Telegram node to receive updates, route based on message type (text, command, callback query), and send formatted responses (text, buttons, inline keyboards).","intents":["I want to build a Telegram bot that answers questions using AI without managing a separate bot server","I need a bot that executes commands (/translate, /summarize, /analyze) with AI processing","I want to create a notification bot that sends alerts from my application to Telegram","I need a bot with inline buttons and callback queries for interactive workflows"],"best_for":["developers building Telegram bots without managing bot servers","teams automating notifications to Telegram channels","creators building interactive bots with command-driven workflows","small teams using Telegram as a lightweight interface to internal tools"],"limitations":["Webhook-based architecture requires n8n instance to be publicly accessible; no polling fallback for restricted networks","Telegram message size limits (4096 characters) require response chunking for long AI-generated content","No built-in rate limiting; high-volume bots may hit Telegram API rate limits without explicit backoff logic","State management is workflow-level; no distributed session storage for multi-instance deployments","Media handling (photos, documents) is limited; templates primarily handle text messages"],"requires":["Telegram Bot API token (obtained from BotFather)","n8n instance with public URL for webhook configuration","OpenAI or Google Gemini API key for conversational responses","Optional: database or external storage for user state/conversation history"],"input_types":["Telegram messages (text, commands, callback queries)","User IDs and chat IDs (for routing and state tracking)","Message metadata (timestamp, sender, message type)"],"output_types":["Telegram messages (text, formatted with markdown/HTML)","Inline keyboards and buttons (for interactive workflows)","Notifications and alerts sent to Telegram channels"],"categories":["automation-workflow","tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_5","uri":"capability://automation.workflow.discord.integration.templates.with.message.routing.and.ai.responses","name":"discord integration templates with message routing and ai responses","description":"Provides Discord webhook and bot integration templates that listen for messages in specific channels, parse commands and mentions, route to AI processing (OpenAI/Gemini), and post formatted responses with embeds and reactions. Workflows demonstrate conditional routing based on channel, user role, or message content, and integration with external services (database queries, API calls) triggered by Discord messages.","intents":["I want a Discord bot that answers questions in my server using AI without managing a separate bot","I need to route Discord messages to different workflows based on channel or command","I want to create a bot that executes commands (/ask, /summarize, /translate) with AI processing","I need to send formatted Discord embeds and reactions based on workflow outcomes"],"best_for":["gaming communities automating moderation and Q&A","developer communities building internal Discord bots","teams using Discord as a notification hub for application events","creators building interactive Discord experiences without bot server management"],"limitations":["Discord API rate limits (10 requests/10 seconds per channel) require careful request batching","Message content intent requires privileged gateway intent; not available for all bot types","Embed formatting is rigid; complex layouts require multiple messages or external rendering","No built-in permission checking; workflows must manually validate user roles before executing commands","Reaction-based workflows are limited to emoji reactions; no custom interactive components beyond buttons"],"requires":["Discord bot token with appropriate intents (message content, guild messages)","n8n instance with public URL for webhook configuration","OpenAI or Google Gemini API key for conversational responses","Discord server with bot added and appropriate channel permissions"],"input_types":["Discord messages (text, commands, mentions)","User IDs and roles (for permission checking)","Channel IDs (for routing and context)"],"output_types":["Discord messages (text, embeds, formatted responses)","Reactions and emoji responses","Direct messages to users"],"categories":["automation-workflow","tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_6","uri":"capability://automation.workflow.google.drive.and.sheets.integration.with.document.processing.and.data.sync","name":"google drive and sheets integration with document processing and data sync","description":"Provides ~12 templates for automating Google Drive and Sheets workflows: monitoring for new files, extracting text from documents (OCR via Google Vision or Gemini), parsing spreadsheets, syncing data between Sheets and external databases, and generating reports. Workflows use n8n's Google Drive and Sheets nodes, Google APIs for document analysis, and conditional logic for data transformation and routing.","intents":["I want to automatically process uploaded documents (PDFs, images) and extract structured data into Sheets","I need to sync data between Google Sheets and my database in real-time","I want to generate reports by aggregating data from multiple Sheets and exporting as PDF","I need to monitor a Google Drive folder and trigger workflows when new files are uploaded"],"best_for":["teams using Google Workspace for document management and data collection","businesses automating data entry from forms or documents into Sheets","organizations syncing Google Sheets with CRM, ERP, or database systems","teams generating automated reports from Sheets data"],"limitations":["Google Sheets API has cell write limits (60,000 updates/minute); bulk operations may require batching","OCR accuracy depends on document quality; templates lack confidence scoring or manual review workflows","File monitoring relies on polling; real-time change detection requires Google Drive Activity API with higher latency","Complex formulas in Sheets are not preserved during data sync; only values are transferred","Large file processing (>100MB) may timeout; templates assume moderate file sizes"],"requires":["Google Cloud project with Drive and Sheets APIs enabled","OAuth credentials for Google account with Drive/Sheets access","n8n instance with Google Drive and Sheets nodes configured","Optional: Google Vision API for OCR, or Gemini API for document analysis"],"input_types":["Google Drive files (PDFs, images, documents)","Google Sheets (for reading/writing data)","File metadata (name, size, creation date)"],"output_types":["Extracted text and structured data (JSON, CSV)","Updated Google Sheets rows/cells","Generated reports (PDF, Sheets, or exported formats)"],"categories":["automation-workflow","data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_7","uri":"capability://automation.workflow.notion.integration.with.database.sync.and.content.automation","name":"notion integration with database sync and content automation","description":"Provides templates for syncing data between Notion databases and external systems (CRM, ticketing, spreadsheets), automating content creation in Notion (generating pages, database entries), and querying Notion data for reporting. Workflows use n8n's Notion node (API v1), parse Notion database schemas, transform external data to Notion property formats, and handle bidirectional sync with conflict resolution.","intents":["I want to sync my CRM contacts with a Notion database automatically","I need to create Notion pages from form submissions or external data sources","I want to query Notion databases and generate reports or exports","I need to keep Notion and my database in sync without manual updates"],"best_for":["teams using Notion as a knowledge base or project management system","businesses automating data entry from external systems into Notion","organizations syncing Notion with CRM, ticketing, or database systems","creators building Notion-based workflows without manual data entry"],"limitations":["Notion API has rate limits (3 requests/second); high-volume sync requires batching and backoff logic","Property type mapping is manual; templates must explicitly handle Notion's rich property types (select, multi-select, relation, rollup)","Bidirectional sync requires conflict resolution logic; templates lack automatic merge strategies","Notion API doesn't support bulk operations; each database entry requires separate API call","Complex Notion relations and rollups are read-only; workflows cannot programmatically create relations"],"requires":["Notion workspace with API access enabled","Notion integration token (internal integration or OAuth)","n8n instance with Notion node configured","Knowledge of Notion database schema and property types","External system credentials (CRM, database, etc.) for sync"],"input_types":["Notion database entries (via API query)","External data (CRM records, form submissions, database rows)","Notion property schemas (for type mapping)"],"output_types":["Created/updated Notion database entries","Notion pages with generated content","Exported data from Notion (JSON, CSV)"],"categories":["automation-workflow","data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_8","uri":"capability://data.processing.analysis.pdf.and.document.processing.with.ai.extraction.and.generation","name":"pdf and document processing with ai extraction and generation","description":"Provides ~15 templates for PDF processing: extracting text and tables (using PDF parsing libraries or Gemini Vision), classifying documents by type, generating PDFs from templates or data, and routing documents based on content analysis. Workflows use n8n's file handling, Google Gemini or OpenAI Vision for document understanding, and PDF generation libraries for creating reports or forms.","intents":["I want to automatically extract data from uploaded invoices or receipts into a database","I need to classify documents by type (contract, invoice, report) and route to appropriate handlers","I want to generate PDF reports by combining data and templates","I need to extract tables from PDFs and convert to structured data (CSV, JSON)"],"best_for":["finance teams automating invoice and receipt processing","legal teams classifying and organizing contracts","enterprises automating document workflows and data extraction","teams generating automated reports and documents"],"limitations":["PDF text extraction quality varies by document format; scanned PDFs require OCR (Gemini Vision or external service)","Table extraction is imperfect; complex multi-column layouts may require manual verification","PDF generation is limited to simple templates; complex layouts require external PDF libraries or services","Large PDF files (>50MB) may timeout during processing","Handwritten text extraction is unreliable; templates assume printed or digital documents"],"requires":["n8n instance with file handling and HTTP request capabilities","Google Gemini or OpenAI Vision API for document analysis","PDF parsing library (built-in to n8n or external service)","Optional: PDF generation library (e.g., pdfkit, reportlab) for creating documents"],"input_types":["PDF files (uploaded or from cloud storage)","Images of documents (for OCR)","Document templates (for PDF generation)"],"output_types":["Extracted text and structured data (JSON, CSV)","Document classification labels","Generated PDF files"],"categories":["data-processing-analysis","automation-workflow","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-enescingoz--awesome-n8n-templates__cap_9","uri":"capability://automation.workflow.airtable.workflow.automation.with.data.sync.and.record.management","name":"airtable workflow automation with data sync and record management","description":"Provides templates for automating Airtable workflows: syncing data between Airtable and external systems, creating/updating records based on triggers, automating field calculations, and generating reports from Airtable data. Workflows use n8n's Airtable node, handle Airtable's field types (single/multi-select, attachments, linked records), and implement bidirectional sync with conflict resolution.","intents":["I want to sync my CRM data with Airtable for team collaboration","I need to automatically create Airtable records from form submissions or external data","I want to update Airtable fields based on external events or calculations","I need to generate reports or exports from Airtable data"],"best_for":["teams using Airtable for project management and data collaboration","businesses automating data entry from external systems into Airtable","organizations syncing Airtable with CRM, database, or other tools","teams building Airtable-based workflows without manual updates"],"limitations":["Airtable API has rate limits (5 requests/second); bulk operations require batching","Linked records and lookups are complex to sync; templates may require manual relationship mapping","Attachment handling is limited; templates can reference attachment URLs but not upload files directly","Bidirectional sync requires conflict resolution; templates lack automatic merge strategies","Complex field types (formula, rollup) are read-only; workflows cannot programmatically create them"],"requires":["Airtable workspace with API access enabled","Airtable API token","n8n instance with Airtable node configured","Knowledge of Airtable base schema and field types","External system credentials (CRM, database, etc.) for sync"],"input_types":["Airtable records (via API query)","External data (form submissions, database rows, API responses)","Airtable field schemas (for type mapping)"],"output_types":["Created/updated Airtable records","Exported data from Airtable (JSON, CSV)","Synced data to external systems"],"categories":["automation-workflow","data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":42,"verified":false,"data_access_risk":"high","permissions":["n8n instance (self-hosted or cloud) with admin access to import workflows","API keys for target services (OpenAI, Google, Slack, Discord, etc.) depending on template","Basic understanding of n8n workflow structure and node configuration","Network connectivity to external services (Gmail, Telegram, Notion, etc.)","Vector database account (Pinecone, Weaviate, Supabase, or self-hosted Milvus)","Embedding API key (OpenAI, MistralAI, or local embedding model)","LLM API key (OpenAI, Google Gemini, or MistralAI)","Document source (PDF, text files, web pages, or database records)","n8n instance with HTTP request and code node capabilities","Social media platform API credentials (Twitter/X, LinkedIn, Instagram, Facebook)"],"failure_modes":["Templates are JSON-based and require n8n instance to import; no visual drag-and-drop preview before import","API credentials and service-specific configuration must be manually added post-import; templates don't auto-detect available credentials","No built-in versioning or update mechanism; templates are static snapshots that may become stale as service APIs evolve","Limited to n8n's node ecosystem; workflows cannot use external Python/Node.js libraries without custom code nodes","No dependency resolution; complex workflows with 10+ integrations require manual troubleshooting if a single service API changes","Vector database setup and embedding generation incur per-token costs; templates don't include cost optimization strategies","Chunking strategies (fixed-size, semantic, recursive) are hardcoded in templates; no dynamic adjustment based on document type","No built-in reranking or relevance filtering; all retrieved chunks are passed to LLM, potentially increasing token usage","Templates assume synchronous retrieval; no support for async batch embedding or incremental index updates","Limited to single-vector-database patterns; no multi-index or hybrid search (vector + keyword) examples","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.38817370792904227,"quality":0.5,"ecosystem":0.8,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.2,"quality":0.25,"ecosystem":0.1,"match_graph":0.4,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.550Z","last_scraped_at":"2026-05-03T13:59:57.742Z","last_commit":"2026-04-09T17:13:26Z"},"community":{"stars":21832,"forks":5946,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=enescingoz--awesome-n8n-templates","compare_url":"https://unfragile.ai/compare?artifact=enescingoz--awesome-n8n-templates"}},"signature":"Dcn6kHFgRzmzzc0tHJLlqIUf/GYlHIvyeO9CO4fdV85Bf2AQh7RJ8ECEasBkI7i18Umk2Uxc9If71+XHRkS0AA==","signedAt":"2026-06-20T22:58:01.821Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/enescingoz--awesome-n8n-templates","artifact":"https://unfragile.ai/enescingoz--awesome-n8n-templates","verify":"https://unfragile.ai/api/v1/verify?slug=enescingoz--awesome-n8n-templates","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}