Artificial Intelligence – N8N

Simple workflow that processes form submissions with an LLM and sends the result via email.

Scheduled workflow that periodically exports Airtable records and writes them to disk as structured text files.

Automated ingestion pipeline that indexes newly uploaded Google Drive files into a Pinecone vector store.

Reusable calendar-focused sub-agent that executes event-related actions when invoked by other workflows.

MCP server workflow that receives structured mail commands from external agents and executes email delivery via Gmail.

MCP server workflow that exposes a set of external tools for use by AI agents via structured tool calls.

Chat-driven AI agent that interprets user intent and routes requests either to internal reasoning or to external tools via an MCP client.

Chat-driven AI agent that interprets user instructions and delegates mail-related actions to an external MCP server.

Chat-driven AI agent that retrieves context from a vector database and can compose and send emails based on stored mail-related data.

Event-driven workflow that ingests new documents from Google Drive, processes their content, and stores embeddings in a vector database.

Chat-driven AI agent that retrieves context from a vector store, maintains simple conversation memory, and logs interactions to Google Sheets.

Chat-triggered AI agent that processes incoming messages and sends emails using a local language model and basic conversation memory.

Minimal error-handling workflow that triggers on execution failures and sends a notification email.

Scheduled workflow that retrieves emails from the last 24 hours, structures the data, and generates a daily summary using an LLM.

An intelligent email automation workflow that analyzes incoming Gmail messages, filters them using an AI agent, and automatically replies when specific conditions are met.

A simple automation workflow that captures form submissions and automatically creates structured records in Airtable.

An automated email workflow that uses an Airtable trigger and a local LLM via Ollama to generate and send context-aware messages.

An AI agent workflow that dynamically selects and executes predefined prompts from a datatable, enabling structured, reusable, and scalable conversational logic.