Build n8n workflows that download, transform, and send files without losing their contents. Learn how file data differs from JSON, how to preserve attachments, and how to use storage keys or URLs with AI tools and chat messages.
- Fixing attachments lost during data transformation
- Passing uploaded files to AI agent tools
- Displaying generated images in chat
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Manage which n8n instance an MCP session targets when working across production, staging, teams, or clients. Guides instance switching, checks before credential changes, and recovery from unexpected missing data or ambiguous credential writes.
- Switching between production and staging
- Checking the target before credential changes
- Investigating unexpected missing data
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Use n8n-mcp tools to find workflow steps, check settings, and create or update automations. Provides guidance on tool arguments, templates, folders, credentials, and security audits so agents can choose appropriate operations.
- Finding nodes and checking their settings
- Creating and updating workflows
- Finding and deploying workflow templates
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Write Python for n8n Code nodes to transform, filter, aggregate, and validate workflow data. Get guidance on reading input items, returning the required JSON structure, using standard library modules, and avoiding common errors within n8n's Python execution modes.
- Transforming and filtering data in n8n with Python
- Calculating totals and basic statistics
- Extracting and validating text with regular expressions
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Design n8n automations for incoming events, API connections, database synchronization, AI agents, scheduled tasks, and batch processing. Choose a suitable structure, plan error handling, check connections, test results, and review performance when processing large numbers of items.
- Sending form submissions to Slack
- Generating and emailing scheduled reports
- Synchronizing records between databases
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Design AI agents and chatbots in n8n, choosing suitable nodes and connecting models, tools, conversation memory, and structured JSON output. Includes guidance on document retrieval and human approval before tool execution.
- Building a chatbot with conversation memory
- Connecting external tools to an AI agent
- Returning data in a defined JSON format
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Build custom calculation and parsing tools that an n8n AI Agent can call. This skill covers JavaScript or Python inputs, structured arguments, string results, tool descriptions, and fixes for invocation and output errors.
- Adding a calculation tool to an AI Agent
- Defining typed inputs for multiple arguments
- Fixing tool output type errors
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Write JavaScript for n8n Code nodes to aggregate, filter, and transform workflow data. Guidance covers data access, output formats, execution modes, common errors, and performance choices when processing large numbers of records.
- Aggregating and deduplicating multiple records
- Transforming complex API responses
- Fixing data access and return format errors
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Configure n8n nodes by checking which fields each operation needs and which settings reveal additional options. Start with a minimal configuration, validate it, look up unclear properties, and make targeted edits to existing code or text fields.
- Checking required fields when changing a node operation
- Finding why a configuration field is hidden
- Editing part of a long code or text field
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Build reusable parts for n8n workflows instead of copying shared logic. This skill guides typed inputs, consistent outputs, naming, and execution settings so workflows and AI agents can call the same processing steps.
- Sharing common logic across workflows
- Splitting a large workflow into reusable parts
- Exposing shared processing as an AI agent tool
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Find the right specialist guidance for building, editing, testing, or debugging n8n workflows through n8n-mcp. This entry skill explains available tools, connection requirements, credential handling, and checks to perform before activating a workflow.
- Finding the right skill for an n8n task
- Checking settings and connections before activation
- Investigating a workflow that behaves unexpectedly
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Deploy n8n on a Linux server using Docker Compose and Caddy for automatic HTTPS. Covers single-instance setups, workers for parallel execution, secret management, deployment checks, updates, backups, and restoration.
- Installing n8n on a VPS
- Running workflows in parallel with workers
- Publishing n8n with automatic HTTPS
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Interpret n8n validation results and work through fixes for missing settings, broken references, and expression errors. Distinguishes blocking errors from advisory warnings, explains validation profiles, and guides review of automatic fixes and execution failures.
- Understanding validation errors
- Deciding which warnings need attention
- Choosing a validation profile
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Write and troubleshoot n8n expressions, the formulas that pass and transform data between workflow steps. Covers field references, webhook inputs, dates, strings, and choosing between expressions and Code nodes for data transformations.
- Fixing expression syntax errors
- Using webhook data in downstream steps
- Formatting dates and strings
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Add error handling to n8n workflows with connected error outputs, retries, and failure notifications. Return HTTP status codes that explain what went wrong, distinguish invalid requests from service failures, and keep internal error details out of public responses.
- Investigating workflows that fail without notification
- Returning clear errors from webhook APIs
- Retrying temporary network failures
czlonkowski/n8n-mcp☆ 23.1KUpdated Oct 18, 2026
Expert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, organizing workflows into folders, managing credentials, auditing instance security, or using any n8n-mcp tool. Provides tool selection guidance, parameter formats, and common patterns. IMPORTANT — Always consult this skill before calling any n8n-mcp tool — it prevents common mistakes like wrong nodeType formats, incorrect parameter structures, and inefficient tool usage. If the user mentions n8n, workflows, nodes, or automation and you have n8n MCP tools available, use this skill first.
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czlonkowski/n8n-skills☆ 6.5KUpdated Oct 16, 2026
Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, batch processing, or scheduled tasks. Always consult this skill when the user asks to create, build, or design an n8n workflow, automate a process, or connect services — even if they don't explicitly mention 'patterns'. Covers webhook, API, database, AI, batch processing, and scheduled automation architectures. Also use when optimizing a slow workflow or speeding up large-item-count processing (node count, batchSize, all-items vs per-item).
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czlonkowski/n8n-skills☆ 6.5KUpdated Oct 16, 2026
Write JavaScript code in n8n Code nodes. Use when writing JavaScript in n8n, using $input/$json/$node syntax, making HTTP requests with this.helpers / the $helpers global, working with dates using DateTime, troubleshooting Code node errors, choosing between Code node modes, or doing any custom data transformation in n8n. Always use this skill when a workflow needs a Code node — whether for data aggregation, filtering, API calls, format conversion, batch processing logic, or any custom JavaScript. Covers SplitInBatches loop patterns, cross-iteration data, pairedItem, and real-world production patterns. Also use when asked why a Code node or workflow is slow, which execution mode is faster, or how to cut per-item overhead on large datasets. EXCEPTION — for the AI-agent-callable Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode, a tool attached to an AI Agent), use the n8n-code-tool skill instead; it has a different runtime contract.
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czlonkowski/n8n-skills☆ 6.5KUpdated Oct 16, 2026
Build reusable, composable n8n sub-workflows. Use when extracting shared logic, building anything multi-step or reused across workflows, or any workflow over ~10 nodes — and whenever the user mentions sub-workflows, Execute Workflow, reuse, shared/common logic, modular workflows, "Define Below" inputs, waitForSubWorkflow, mode each vs all, or exposing a workflow as an agent tool. Covers typed sub-workflow inputs, all-vs-each execution, verb-first naming for discovery, stateless vs stateful design, and splitting by input shape.
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czlonkowski/n8n-skills☆ 6.5KUpdated Oct 16, 2026
Use when an n8n-mcp account targets more than one n8n instance — i.e. the `n8n_instances` tool is available, the user mentions multiple n8n instances or environments (prod vs staging, several teams or clients), several agents or chats work on one account in parallel, a workflow / datatable / credential / execution call returns an unexpected NOT_FOUND or reads data you don't recognize, or a call is refused with `INSTANCE_AMBIGUOUS` or `INSTANCE_NOT_FOUND`. Covers naming the target instance on each call with the `instance` argument, setting the default with `switch`, verifying the target before high-stakes work — credential writes above all — and recovering from misroutes and fail-closes. Always consult this skill before operating on a specific instance, before any credential create/update/delete on a multi-instance account, or when a call hits the wrong/empty data or an instance error.
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czlonkowski/n8n-skills☆ 6.5KUpdated Oct 16, 2026
Interpret validation errors and guide fixing them. Use when encountering validation errors, validation warnings, false positives, operator structure issues, or need help understanding validation results. Also use when asking about validation profiles, error types, the validation loop process, or auto-fix capabilities. Consult this skill whenever a validate_node or validate_workflow call returns errors or warnings — it knows which warnings are false positives and which errors need real fixes.
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czlonkowski/n8n-skills☆ 6.5KUpdated Oct 16, 2026
Use when building, editing, validating, testing, or debugging an n8n workflow through the n8n-mcp MCP server — designing a flow, configuring a node, writing an expression or Code node, wiring credentials, or fixing one that misbehaves. The entry-point skill for the n8n-mcp-skills pack: it routes you to the right specialist skill, gives working knowledge of every n8n-mcp tool from turn one, and states the rules that keep workflows from breaking in production. Always consult it first on any n8n, workflow, node, or automation task — even a quick one-off, and even when the user names no skill — because n8n's surface drifts between versions and the specialist skills prevent silent failures.
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czlonkowski/n8n-skills☆ 6.5KUpdated Oct 16, 2026
Handle files and binary data in n8n correctly. Use when working with files, images, PDFs, attachments, uploads or downloads, base64, vision/multimodal input, or when an AI agent needs a file as tool input or output — and whenever the user mentions $binary, binaryPropertyName, "read the PDF", "attach the file", "send the image", Merge losing binary, or a CDN for chat images. Covers the $binary vs $json split, reading/writing binary, keeping binary alive across transforms with Merge, the agent-tool binary boundary, and the CDN/URL requirement for chat surfaces.
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czlonkowski/n8n-skills☆ 6.5KUpdated Oct 16, 2026
Design n8n AI agents the right way. Use when building or editing any @n8n/n8n-nodes-langchain.* AI node — an AI Agent, LLM chain, Text Classifier, or Information Extractor — and whenever the user mentions AI agents, LLM with tools, tool calling, $fromAI, system prompts, agent memory, sessionId, structured/JSON output, output parser, RAG, vector store, a chat assistant/bot, or human-in-the-loop review. Covers Agent-vs-chain-vs-classifier choice, the model/memory/tools/outputParser slots, tool names/descriptions as prompt, structured output with autoFix, memory, RAG, human review, and chat topologies.
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czlonkowski/n8n-skills☆ 6.5KUpdated Oct 16, 2026