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Build your own N8N workflows MCP server

JimleukJimleuk
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2/3/2026
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This n8n template shows you how to create an MCP server out of your existing n8n workflows. With this, any MCP client connected can get more done with powerful end-to-end workflows rather than just simple tools.

Designing agent tools for outcome rather than utility has been a long recommended practice of mine and it applies well when it comes to building MCP servers; In gist, agents to be making the least amount of calls possible to complete a task.

This is why n8n can be a great fit for MCP servers! This template connects your agent/MCP client (like Claude Desktop) to your existing workflows by allowing the AI to discover, manage and run these workflows indirectly.

How it works

  • An MCP trigger is used and attaches 4 custom workflow tools to discover and manage existing workflows to use and 1 custom workflow tool to execute them.
  • We'll introduce an idea of "available" workflows which the agent is allowed to use. This will help limit and avoid some issues when trying to use every workflow such as clashes or non-production.
  • The n8n node is a core node which taps into your n8n instance API and is able to retrieve all workflows or filter by tag. For our example, we've tagged the workflows we want to use with "mcp" and these are exposed through the tool "search workflows".
  • Redis is used as our main memory for keeping track of which workflows are "available". The tools we have are "add Workflow", "remove workflow" and "list workflows". The agent should be able to manage this autonomously.
  • Our approach to allow the agent to execute workflows is to use the Subworkflow trigger. The tricky part is figuring out the input schema for each but was eventually solved by pulling this information out of the workflow's template JSON and adding it as part of the "available" workflow's description. To pass parameters through the Subworkflow trigger, we can do so via the passthrough method - which is that incoming data is used when parameters are not explicitly set within the node.
  • When running, the agent will not see the "available" workflows immediately but will need to discover them via "list" and "search". The human will need to make the agent aware that these workflows will be preferred when answering queries or completing tasks.

How to use

  • First, decide which workflows will be made visible to the MCP server. This example uses the tag of "mcp" but you can all workflows or filter in other ways.
  • Next, ensure these workflows have Subworkflow triggers with input schema set. This is how the MCP server will run them.
  • Set the MCP server to "active" which turns on production mode and makes available to production URL.
  • Use this production URL in your MCP client. For Claude Desktop, see the instructions here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/#integrating-with-claude-desktop.
  • There is a small learning curve which will shape how you communicate with this MCP server so be patient and test. The MCP server will work better if there is a focused goal in mind ie. Research and report, rather than just a collection of unrelated tools.

Requirements

  • N8N API key to filter for selected workflows.
  • N8N workflows with Subworkflow triggers!
  • Redis for memory and tracking the "available" workflows.
  • MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download

Customising this workflow

  • If your targeted workflows do not use the subworkflow trigger, it is possible to amend the executeTool to use HTTP requests for webhooks.
  • Managing available workflows helps if you have many workflows where some may be too similar for the agent. If this isn't a problem for you however, feel free to remove the concept of "available" and let the agent discover and use all workflows!

n8n AI Agent with Model Context Protocol (MCP) Server

This n8n workflow demonstrates how to build a flexible AI agent that can interact with various tools, including other n8n workflows, using the Model Context Protocol (MCP). It features a conversational interface and the ability to dynamically route tasks based on user input.

What it does

This workflow acts as an MCP server, receiving chat messages and processing them through an AI agent.

  1. Listens for Chat Messages: The workflow is triggered by an incoming chat message via the MCP Server Trigger node.
  2. Initializes AI Agent: An AI Agent node is configured with a Simple Memory and an OpenAI Chat Model to process the incoming message, maintain conversation history, and decide on the next action.
  3. Tool Integration: The AI Agent is equipped with a Call n8n Workflow Tool. This tool allows the AI to execute other n8n workflows, effectively extending its capabilities.
  4. Conditional Logic (Implicit): The AI Agent, based on its training and the tools available, implicitly decides whether to use the Call n8n Workflow Tool or respond directly.
  5. Handles Workflow Tool Output: If the Call n8n Workflow Tool is used, its output is processed.
  6. Responds to Chat: The final response from the AI Agent (either a direct answer or the result of a tool execution) is sent back as a chat message.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance (self-hosted or cloud).
  • OpenAI API Key: Required for the OpenAI Chat Model to function. This should be configured as an n8n credential.
  • Model Context Protocol (MCP) Client: An external application or another n8n workflow that acts as an MCP client to send chat messages to this server workflow.
  • Sub-workflows (Optional): If you intend for the Call n8n Workflow Tool to execute specific n8n workflows, those workflows must exist and be configured to accept input from this agent.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Locate the OpenAI Chat Model node.
    • Set up an OpenAI API Key credential if you haven't already.
  3. Activate the Workflow: Enable the workflow to start listening for incoming MCP chat messages.
  4. Configure Call n8n Workflow Tool:
    • Open the Call n8n Workflow Tool node within the AI Agent.
    • Specify the target n8n workflow(s) that the AI agent should be able to call. You will need the Workflow ID of the sub-workflow(s).
  5. Interact with the MCP Server:
    • Use an MCP client (e.g., another n8n workflow with an MCP Client Tool node, or a custom application) to send chat messages to this workflow.
    • The AI agent will process the message, potentially call a sub-workflow, and respond.

This workflow provides a robust foundation for building intelligent, extensible AI agents within n8n, leveraging the power of the Model Context Protocol for seamless communication and tool execution.

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