N8n Agents Official logo

N8n Agents Official

Organization
n8n-io
n8n-agents-official

Use when the user wants an agent, assistant, or bot in n8n, or is building, editing, testing, publishing, or debugging a first-class n8n Agent. Covers choosing an Agent vs a workflow vs the AI Agent node, the Agent MCP tools (create_agent, mutate_agent, validate_agent, call_agent, publish_agent, update_agent_integration), Agent config JSON, tools and approvals, skills, sub-agents, model routing, knowledge files, vector stores, memory and sessions, Slack / Telegram / Discord / Linear / n8n Chat channels, scheduled tasks, the Message an Agent node, and reading Agent sessions and traces. Triggers on "build me an agent", "assistant", "chatbot", "Slack bot", "Telegram bot", "agent skills", "sub-agent", "knowledge base", "agent memory", "session", "Message an Agent", "publish the agent", or any Agent tool call.

Overview

Publishern8n-io
Repositoryskills
Skill namen8n-agents-official
Stars
551
Forks
80
Bundled files
12
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 12 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by n8n-io on GitHub. Read the source before you install it.

Installation

Install the N8n Agents Official AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/n8n-io/skills/tree/main/skills/n8n-agents-official
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/n8n-io/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/n8n-agents-official .claude/skills/n8n-agents-official
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable N8n Agents Official in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads N8n Agents Official on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so N8n Agents Official is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

n8n Agents

A first-class n8n Agent is a saved resource with its own instructions, model, tools, skills, sub-agents, memory, channels, scheduled tasks, versions, and spend limits. It is configured as JSON through the Agent MCP tools, never with Workflow SDK code. The AI Agent node inside a workflow is a different thing, covered by n8n-ai-nodes-official.

Agents are generally available. The UI shows a Preview tag because they change often and some features you might expect aren't there yet. They aren't ready for Enterprise yet: an Enterprise instance may have them enabled, but don't assume it. If create_agent isn't in your tool list, Agents aren't enabled on this instance. Say so and offer a workflow instead of guessing.

Non-negotiables

  1. Always send a memory block when creating over MCP: "memory": { "enabled": true, "storage": "n8n" }. The UI adds it on every save. create_agent saves exactly what you send, and without it the Agent forgets the previous turn even inside one session (verified live).
  2. Never publish without the user's explicit OK. A built Agent is a draft. Configuring a channel on an already published Agent connects it immediately, so confirm that too.
  3. Publish what the Agent calls. Workflow tools need a When Executed by Another Workflow trigger, the same project, and a published workflow (validate_agent reports it). Saved sub-agents must be published too, and nothing checks that: validation and publishing pass, then production delegation fails and the parent quietly answers on its own.
  4. Approval on anything that sends, changes, deletes, or spends, and know what the approver will see. See references/APPROVALS.md.
  5. One mutate_agent per change, always with the latest configHash. A stale hash returns stale_config: call get_agent and retry.

Agent, workflow, or AI Agent node?

Decide before calling any build tool. The first question is the "say it out loud" test.

You can...Build
Say every step before the request arrives, none needs judgmentWorkflow
Say every step, one needs judgment (label, extract, summarize, write)Workflow with an AI step: Text Classifier, Information Extractor, chain, or AI Agent node (n8n-ai-nodes-official)
Not say the steps until you see the request, and people talk to it or it acts on its ownFirst-class n8n Agent
Not say the steps, but one of the limits below appliesAI Agent node in a workflow
Not say the steps, and a fixed pipeline also needs the same brainFirst-class Agent, called from the workflow with Message an Agent. The agent decides, the workflow acts

"Build me an agent" or "assistant" means a first-class Agent unless a limit applies. A Chat Trigger plus an AI Agent node is not a substitute for a requested Agent. If a request is really a fixed trigger plus fixed steps, explain the mismatch and ask before building a workflow instead.

Current limits that point to the AI Agent node

NeedWhy an Agent can't do it todayUse instead
Custom approval message, or the approver must see the parameters in SlackApproval is on/off with a fixed message. Channel cards show the tool name onlyA workflow tool that runs its own send-and-wait approval with the values (can post in the same Slack thread)
Trigger or node data mapped exactly into a tool parameterTool expressions only see the model's own arguments (verified live for node and workflow tools)AI Agent node, or Message an Agent with structured output and downstream nodes doing the mapping
One conversation shared by a native channel and workflowsChannel threads and Message an Agent session keys live in separate namespacesA shell workflow on the platform's trigger, calling the Agent with Message an Agent
Approval inside a Message an Agent callFails with "Suspend/resume is not supported in workflow execution context"Gate the action in the calling workflow

MCP build sequence

  1. get_agent_builder_reference once. Its configSchema is the source of truth for field names; trust it over this skill when they differ.
  2. search_projects, then discover_agent_assets (models, integrations, workflows, subagents, mcpServers), list_credentials, and search_nodes with usage: "agentTool" + get_node_types for node tools.
  3. create_agent with model, credential, instructions, memory block, and ordinary tools. Skills, tasks, and custom tools come after, through mutate_agent, because they need server-generated ids.
  4. mutate_agent, one operation per call. skill.upsert doesn't change configHash; config patches do.
  5. validate_agent until valid: true and missing is empty.
  6. One representative call_agent. It runs the draft through Preview with real tools, so side effects happen: if any tool without approval sends, writes, or pays, ask the user before the test. Every returned approval goes to the human; resume each with its continuation.
  7. Report the draft with the url from validate_agent, plus the session link (see references/SESSIONS_AND_DEBUGGING.md), and ask whether to publish.
  8. publish_agent only on an explicit yes. Channels: update_agent_integration (references/CHANNELS.md).

Details on every operation, error code, and version tool: references/MCP_BUILD.md.

Where depth lives

FileRead when
references/MCP_BUILD.mdAny mutate_agent operation, error codes, versions, revert, delete, availableInMCP
references/CONFIG.mdWriting or reviewing Agent JSON: every field, limits, defaults, what is versioned
references/TOOLS.mdNode, workflow, custom, MCP server, and built-in tools, input modes, what expressions can see
references/APPROVALS.mdAdding approval, what each surface shows, where approval can't happen, custom approval through a workflow tool
references/SKILLS.mdAdding Agent skills: how loading works, writing descriptions, references
references/SUB_AGENTS.mdDelegation, saved vs inline sub-agents, model routing by difficulty
references/KNOWLEDGE.mdUploaded knowledge files vs external vector stores
references/MEMORY.mdMemory kinds, session scopes, session keys
references/CHANNELS.mdSlack, Telegram, Discord, Linear, n8n Chat, or "native channel or shell workflow?"
references/TASKS.mdScheduled tasks
references/MESSAGE_AN_AGENT.mdCalling an Agent from a workflow
references/SESSIONS_AND_DEBUGGING.mdAnything went wrong, or the user asks where to see what the Agent did

For a chat bot built as a workflow shell (platforms without a native channel, slash commands, custom routing), the shell patterns live in n8n-ai-nodes-official references/CHAT_SURFACE_PATTERNS.md, section "Core as Message an Agent". Its one rule that can't wait: on surfaces that deliver the bot's own messages (Slack, Discord), a shell that posts replies must filter out the bot's user ID right after the trigger, or it triggers itself forever.

Writing instructions

Instructions are the system prompt. Same split as the node: persona, rules, output format, and inter-tool flow go in instructions; how to call a specific tool goes in that tool's description. Long procedures the Agent needs only sometimes belong in a skill, which costs tokens only when loaded. Say where to deliver results ("post the summary in #ops"), because a scheduled run has no one to reply to.

Anti-patterns

Anti-patternWhat goes wrongFix
create_agent without memoryAgent forgets the previous turn even in one sessionSend { "enabled": true, "storage": "n8n" }
Chat Trigger + AI Agent node when the user asked for an agentLoses channels, sessions, approvals, versions, tasks, and budgetsFirst-class Agent, unless a limit applies
Publishing because validation passedThe user didn't approve a live Agent, and channels go live with itReport the draft and ask
Saved sub-agent left unpublishedProduction delegation fails silently; the parent answers without itPublish children before the parent goes live
Expression in a tool input that reads $('Webhook') or $json.<trigger field>Only the model's arguments are visible, so the value is empty or wrongPass it through the message, or keep the mapping in a workflow
Approval on a tool the Agent calls under Message an Agent or a taskRun fails, or parks with no one to answerGate in the calling workflow; give tasks only safe tools
Same Message an Agent session key for two Agents in a project (e.g. both keyed on a bare Telegram id)Keys are project-wide, not per Agent: the second Agent fails with "Failed to create the agent execution record"Prefix keys per Agent: support-<telegramId>
Skill body says "read references/x.md" vaguelyThe model often skips it"Load references/x.md with load_skill (filePath) before answering"
Integrations set through config.patchRejectedupdate_agent_integration
Slack connected with a credential built for a Slack TriggerPasses every check, receives nothingManaged setup, or an app whose request URL points at this Agent

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the N8n Agents Official AI skill do?

Use when the user wants an agent, assistant, or bot in n8n, or is building, editing, testing, publishing, or debugging a first-class n8n Agent. Covers choosing an Agent vs a workflow vs the AI Agent node, the Agent MCP tools (create_agent, mutate_agent, validate_agent, call_agent, publish_agent, update_agent_integration), Agent config JSON, tools and approvals, skills, sub-agents, model routing, knowledge files, vector stores, memory and sessions, Slack / Telegram / Discord / Linear / n8n Chat channels, scheduled tasks, the Message an Agent node, and reading Agent sessions and traces. Trigg...

Why use N8n Agents Official on TypingMind?

Because you install it once and use it with any model. N8n Agents Official is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install N8n Agents Official in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/n8n-io/skills/tree/main/skills/n8n-agents-official. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use N8n Agents Official?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with N8n Agents Official?

As many as you like. As long as a model supports skills, you can use N8n Agents Official with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the N8n Agents Official AI skill free?

Yes. It is published on GitHub by n8n-io under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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