The most used nodes

Expose the flow's actions through a server that AI clients can connect to and call as tools.

Activepieces1 action1 trigger

Steer how a run proceeds, such as repeating steps over a list, branching, or stopping the run early.

Activepieces3 actions

Change text along the way: find and replace, split, join, trim, and switch upper or lower case.

Activepieces12 actions

Call another flow and use what it returns, or let this flow be called by others as a reusable piece.

Activepieces3 actions1 trigger

Reacts to messages sent to a bot and sends replies, files, or other chat actions back to users in that messaging app.

Activepieces20 actions1 trigger

Pause the run until a person approves or rejects, then continue down the path that matches their answer.

Activepieces2 actions

Send, search, and read messages in a Google email account, and start the flow when mail arrives.

Activepieces11 actions4 triggers

Create, read, convert, zip, and unzip files, and check their details, while passing them between steps.

Activepieces7 actions

Reshape data by renaming fields, picking out parts, and building new objects for the steps that follow.

Activepieces1 action

Read rows from an online spreadsheet, append new rows, or update existing cells as part of the flow.

Activepieces27 actions4 triggers

Reach many different AI models through a single service to produce text, code, or images.

Activepieces9 actions

Create a task for a team member and wait for them to review, approve, or do the manual work needed.

Activepieces3 actions

Work with PDF documents, such as pulling out text or combining, splitting, and creating pages.

Activepieces9 actions

Do basic arithmetic on two numbers (add, subtract, multiply, divide) or produce a random number for later steps.

Activepieces6 actions

Generate text, images, audio, or embeddings from hosted models for drafting, transcribing, or search.

Activepieces19 actions

Send prompts to a hosted large language model and use the returned text or answers in later steps.

Activepieces1 action

Watch a feed address for newly published items and read their titles, links, and content.

Activepieces2 triggers

Send WhatsApp messages, read and update contacts, and drive chat replies through a WAHA server.

Activepieces41 actions5 triggers

Sends prompts to Google's Gemini models and returns generated text, images, video, or spoken audio for later steps to use.

Activepieces11 actions

Sends email messages out of a flow by connecting to a mail server with your own credentials, setting recipients, subject and body.

Activepieces1 action

Generate text and reason over long inputs using Claude models.

langgeniusmodel

Search the web and pull the raw text out of result pages, so a model can read fresh sources.

langgeniustool

Read, filter, and edit JSON with path expressions so a flow can pull out or reshape specific fields.

langgeniustool

Call models deployed in your own Microsoft cloud subscription for chat, embeddings, and related tasks.

langgeniusmodel

Connect to a self-hosted inference server to run open models for generation, embeddings, and reranking.

langgeniusmodel

Route requests to many commercial and open-source models through one gateway and a single key.

langgeniusmodel

Generate text, create embeddings, and turn text into spoken audio with one hosted model family.

langgeniusmodel

Convert documents such as PDFs into machine-readable markdown or JSON so later steps can extract their content.

langgeniustool

Fetch web pages as clean text, search the web, and prepare content for models to read.

langgeniustool

Crawl a whole site or scrape single pages and return the page content as structured text.

langgeniustool

Run a web search query and get back result snippets along with the matching page content.

langgeniustool

Use GLM-family hosted models for chat, text generation, and embeddings.

langgeniusmodel

Pull matching pieces of text out of a string using a pattern.

langgeniustool

Turn markdown into DOCX, PPTX, XLSX, PDF, PNG, SVG, HTML, notebook, CSV, JSON, XML or wiki files, and save code blocks as source files.

bowenliang123tool

Read and act on repositories, issues, and other data held in a hosted source code service.

langgeniustool

Add embedding and reranking models for building search and retrieval steps.

langgeniusmodel

Post messages into a workplace chat group through its bot.

langgeniustool

Send messages to a team group chat through its robot webhook.

langgeniustool

Run text embedding models on a fast self-hosted endpoint for search and retrieval steps.

langgeniusmodel

Search the web through a privacy-focused engine and return the results to the flow.

langgeniustool

Upload, download, copy, move, share and search files and folders in a Google cloud drive.

n8n

Send a prompt, with the incoming data filled in, to a connected language model and return its reply in one straight pass with no tools.

n8n

Supply a Google Gemini chat model, with its key and settings, as the brain that an agent, chain or extractor step uses.

n8n

Keep the last few turns of a conversation in memory and feed them back to the model so it remembers recent context per chat session.

n8n

Send a plain text or HTML message with attachments through any SMTP mail server, without being tied to one mail provider.

n8n

Supply a chat model served through OpenRouter, giving steps access to many vendors' models behind one key.

n8n

Create, read, update, delete and search records in a hosted database table, so a base can act as input or storage.

n8n

Supply an Anthropic Claude chat model, with its key and settings, as the brain that an agent, chain or extractor step uses.

n8n

Turn incoming files or text into document chunks that embedding and vector store steps can index or search.

n8n

Use Google Gemini directly for single jobs such as text replies, image and video handling, audio transcription and file uploads.

n8n

Create and update pages, blocks and database entries in a workspace wiki, and search or read existing content.

n8n

Turn text into OpenAI numeric vectors that a vector store or retriever step uses for similarity search.

n8n

Pull values out of HTML with CSS selectors, or build and tidy HTML markup from the data flowing through.

n8n

Run SQL queries against a Postgres database, and insert, update, upsert, select or delete rows in its tables.

n8n

Pull named fields out of messy text with a language model and hand them on as clean structured values.

n8n

Create, update, delete and list calendar events, and check when someone is free or busy.

n8n

Expose another saved automation as a tool an agent can call with arguments, getting its result back as part of the reasoning.

n8n

Send text, template and media messages to customers over the business messaging cloud API and handle incoming ones.

n8n

Supply a chat model hosted on Groq, giving steps a fast low-latency brain for agents, chains and extractors.

n8n

Create documents and read or insert and replace their text, so written content can be generated and updated automatically.

n8n