Analyze Tradingview.Com Charts With Chrome Extension, N8N And OpenAI
AI Research RAG and Data Analysis workflow template
Free community n8n agent templates to level up your workflow.
AI Research RAG and Data Analysis workflow template
AI ML workflow template
General workflow template
00 workflow template
General workflow template
AI Research RAG and Data Analysis workflow template
AI ML workflow template
General workflow template
00 workflow template
n8n agents are pre-built, import-ready automation blueprints forn8n, the open-source workflow automation platform. Each n8n agent is a JSON file that describes a complete graph of nodes: triggers that start the run, language-model nodes that reason over the input, memory nodes that keep conversation context, tool nodes that call APIs or search the web, and output nodes that reply, write to a database, or trigger the next system. Instead of wiring all of that up from a blank canvas, you download one of then8n agents templates on this page, import it into your own n8n instance, add your API keys, and you have a working AI agent in minutes.
The term covers two related ideas that people search for together.n8n agents AI setups use a large language model as the brain of the workflow, so the automation can classify tickets, draft replies, extract structured data from messy text, or hold a multi-turn conversation. Classicn8n workflows, meanwhile, are deterministic automations: when a webhook fires or a schedule triggers, a fixed sequence of steps runs. The most powerful templates on this hub combine both styles into agentic workflows, where an AI model plans the steps dynamically but still calls the same reliablen8n workflows automation nodes for Gmail, Slack, Postgres, Google Sheets, and hundreds of other integrations.
What makes the best n8n agents in 2026 different from the simple chatbot demos of previous years? Three things: memory, tools, and retrieval. The standout n8n agents 2026 templates pair a chat trigger with a vector store for retrieval-augmented generation (RAG), so the agent answers from your docs instead of hallucinating. They give the model real tools — HTTP requests, code execution, calendar lookups, CRM writes — and guardrails such as output parsers and human-in-the-loop approval steps. Compared with many earlyn8n agents 2025 examples that were essentially single-prompt chains, the current generation runs loops: the agent observes a result, decides the next action, and repeats until the task is done. Browse the grid above and look for templates tagged with RAG, chatbot, or assistant to find these patterns.
Every template in this collection is free: there is no paywall and no account required to preview the JSON. These are genuinelyfree n8n workflows — click any card to preview the workflow definition, then copy the JSON or download it and import it via n8n'sImport from File option. Because the library aggregatesn8n workflows free contributions from across the community, you get coverage that no single author could maintain: customer-support chatbots, lead qualification and enrichment flows, meeting-notes summarizers, SEO content pipelines, invoice and document extractors, social-media schedulers, and data-sync jobs between tools like Notion, Airtable, and Postgres. If you are looking foruseful n8n workflows to automate your first real task this week, start with one template that mirrors a job you already do manually, get it running, then adapt it.
All templates here are sourced from public GitHub n8n workflowsrepositories, and that openness is a feature. When you browsen8n agents GitHub projects, you can inspect every node before you run anything — no hidden API calls, no obfuscated logic. Fixes and improvements flow back upstream, so popular github n8n workflows repos get steadily more reliable as the community hardens credentials handling, error paths, and version compatibility. Each card on this page links to its raw JSON on GitHub, so you can diff versions, pin a known-good revision, or fork a workflow and make it your own. For teams evaluating n8n workflows GitHub options versus closed template marketplaces, the auditability of open JSON is usually the deciding factor.
If you are new to the ecosystem, the fastest way to learn is by reading realn8n workflows examples. A beginner-friendly example is a scheduled flow that fetches new rows from a spreadsheet, summarizes them with an LLM node, and posts the digest to Slack — it teaches triggers, expressions, and credentials in one sitting. Intermediate n8n workflows templates add branching, merging, error workflows, and sub-workflows that keep large automations maintainable. Advanced agentic examples go further: a support agent that searches a vector database and your help center before drafting a reply, or a research agent that loops over search results, scrapes pages, and compiles a cited brief. Together these examples show the full ladder from deterministic automation to autonomous behavior, and every rung is represented in the template grid above.
Using any template takes four steps. First, find a workflow in the grid and preview its JSON to confirm it matches your n8n version and the integrations you have. Second, download the file and import it into n8n. Third, reconnect the credential placeholders — OpenAI or another model provider, plus whatever services the flow touches — because credentials are never shipped inside shared templates. Fourth, run the workflow once with test data, watch the execution log node by node, and adjust prompts, filters, and schedules to fit your needs. Mostbest n8n workflows for production also deserve an error-handling path and a pinned test execution, both of which you can study in ourn8n automation guides. That is the whole loop: discover, import, connect, and adapt.
Yes — and the reason is leverage. Knowing how to assemblen8n workflows automation turns every new AI model release into an upgrade for systems you already own, rather than a reason to migrate platforms. Unlike closed automation tools, n8n is self-hostable, so your credentials and data stay on your infrastructure while you still benefit from hundreds of community nodes. The collection on this page exists to flatten the learning curve: instead of starting from an empty canvas, you start from workingn8n agents templates built by people who already solved your problem, and you learn the platform by modifying something real. Pick one free template today, import it, and you will understand more about agentic automation in an afternoon than weeks of tutorials could teach.
n8n workflows are visual automation blueprints made of triggers, actions, and logic nodes. Each workflow is stored as a JSON file you can import into n8n, where it runs on a schedule, via webhook, or on demand — connecting apps like Gmail, Slack, Postgres, and AI models into one automated process.
Preview a template on this page, download its JSON, and import it into your n8n instance with Import from File. Then reconnect the credential placeholders (for example your OpenAI key and any app accounts), run the workflow once with test data, and adjust the prompts, filters, and schedule to fit your needs.
Yes. n8n ships dedicated AI nodes — language models, memory, output parsers, vector stores, and tool-calling agents — alongside 400+ regular integrations. That combination lets you build AI workflows such as RAG chatbots, ticket classifiers, document extractors, and research assistants without writing backend code.
n8n itself is open source and free to self-host, and every n8n agents template on this hub is free to download. You only pay for the third-party services a workflow calls, such as your LLM provider or vector database — many of which offer free tiers that are enough to get started.
Yes, n8n is well suited to agentic workflows. Its AI Agent node lets a language model plan multi-step work, call tools (APIs, databases, web search, code), observe the results, and loop until the task is complete. Many of the best n8n agents in this collection demonstrate exactly that observe-act-repeat pattern.
n8n AI agents are workflows where a language model acts as the decision-maker instead of following a fixed path. The agent receives a goal, picks from connected tools, executes steps, and keeps going until the job is done — for example resolving a support ticket by searching docs, checking order status, and drafting a reply.
An n8n AI agent combines four parts: a trigger that starts the run, a model node that reasons, memory that keeps conversation context, and tool nodes that take real actions. On each iteration the model decides which tool to call next based on the results so far, and an output parser structures the final answer.
Absolutely. Add an AI Agent node to any workflow, connect a chat or webhook trigger, attach a model credential plus memory, and give the agent tools such as HTTP requests or database queries. Starting from one of the free n8n agents templates on this page is the fastest route — import it, then customize the prompt and tools.
Right here: this hub curates free n8n workflow templates from public GitHub repositories, each with a JSON preview, one-click copy, and download. You can also find n8n workflows on GitHub directly and in n8n's official template library — but this page aggregates the best n8n workflows in one searchable grid.
Yes — every template listed on this page is a free n8n workflow. The collection focuses on community-shared, open-source JSON templates, so you can preview, copy, and import them at no cost. Many GitHub n8n workflows from the community are likewise free and MIT-style licensed.
That is their primary purpose. n8n workflows automation covers scheduled reports, webhook-driven integrations, data syncing between apps, lead enrichment, support triage, content pipelines, and AI-powered tasks like summarization and classification. Start with one template that mirrors a manual task you already do, then expand from there.
Yes. Learning n8n in 2026 gives you leverage: every new AI model becomes an upgrade for automations you already own, and because n8n is self-hostable your data stays on your infrastructure. Importing a working template from this hub and adapting it teaches the platform faster than starting from a blank canvas.