n8n MCP Server

Overview

The Leonardsellem n8n MCP Server bridges the gap between AI assistants and the powerful automation engine n8n. By exposing a rich set of tools, resources, and prompts through the Model Context Protocol (MCP), it lets conversational agents query, modify, and execute n8n workflows directly from natural language interactions. This eliminates the need for developers to write custom integrations or manually interact with n8n’s REST API, enabling rapid prototyping and seamless workflow orchestration within AI‑driven applications.

At its core, the server offers a comprehensive workflow management toolkit. AI assistants can list all available workflows, retrieve detailed metadata for a particular workflow, create new ones, update existing definitions, and delete obsolete items. Activation controls allow turning workflows on or off without touching the n8n UI, while execution commands let assistants trigger a workflow and monitor its progress. The ability to stop a running execution provides safety nets for long‑running or erroneous processes, giving developers fine‑grained control over automation life cycles.

Complementing workflow manipulation is a robust execution management layer. Assistants can request the status of individual executions, enumerate all runs for a given workflow, and even stop them mid‑flight. This is particularly valuable in debugging scenarios where an AI assistant needs to surface real‑time execution data or roll back a faulty run. The server’s resources expose these capabilities as simple URLs (e.g., ), which can be embedded directly into prompts or user interfaces, making the data instantly consumable by downstream systems.

Real‑world use cases abound. In a customer support setting, an AI assistant could automatically trigger a “ticket‑creation” workflow when a new issue is reported, then report back the execution status and any generated ticket ID. In DevOps pipelines, a chatbot could start a deployment workflow, monitor its progress, and alert the team upon completion—all without leaving the chat. For data engineers, the server enables on‑demand data ingestion or transformation jobs to be launched from a conversational interface, streamlining ETL processes and reducing context switches.

The server’s integration with AI workflows is straightforward: once registered, the MCP client can invoke any of the exposed tools or query resources as if they were native language commands. Because MCP preserves context across interactions, an assistant can remember a workflow ID from a previous conversation and later retrieve its status or trigger another run. This continuity empowers developers to build sophisticated, stateful automation experiences that feel natural and intuitive.

In summary, the Leonardsellem n8n MCP Server transforms n8n from a standalone automation platform into an AI‑friendly service. By providing declarative tools, actionable resources, and real‑time execution insights, it empowers developers to weave complex workflows into conversational agents, dramatically accelerating the creation of intelligent, automated business processes.