Using the n8n-mcp Skills

This is a router, not a reference. It tells you which skill owns the rules for what you're about to do. The skill bodies hold the actual guidance — invoke them with the Skill tool. When in doubt, load more skills rather than fewer.

The community n8n-mcp server and n8n itself move faster than any model's training cutoff. Tool names, parameters, node typeVersions, and default behaviors drift between releases. When you spot drift — a tool a skill names doesn't exist, a parameter shape doesn't match what get_node returns, behavior differs from what a skill describes — trust the live tool, tell the user, and suggest updating the pack and the instance.

Non-negotiables

Three rules with no exceptions. Each one prevents a class of workflow that looks correct but breaks in production.

1. Invoke the relevant skill before any n8n action — not just before MCP calls. Before writing an expression, configuring a node, designing a workflow, wiring a connection, or writing Code, invoke the matching skill. The PreToolUse hooks remind you on the highest-impact tool calls only when the plugin bundle is installed; on Claude.ai (plain skill uploads, no hooks) the responsibility is entirely yours.
2. Validate AND verify before activating. Run validate_workflow (or n8n_validate_workflow by id) before you activate, and call n8n_get_workflow after every create or update to inspect the connections object. Validation alone misses silently dropped wires, Merge index off-by-one, and error outputs that were never wired. Validation passing means the JSON is well-formed — not that the workflow is correct.
3. Secrets never go in text fields. Tokens, API keys, and passwords always go through the n8n credential system. If no native node exists, use the HTTP Request node with the official credential type. A Set node holding a token referenced via {{ $json.token }} is a leak with extra steps. See n8n-mcp-tools-expert.

Lean on skills, not training data

n8n changes constantly. "Remembered" parameter names are often silently wrong — they validate as plain strings and then do nothing at runtime. Trust the skills and the live tools (get_node, search_nodes, tools_documentation) over recollection. If a skill contradicts your memory, trust the skill. If get_node contradicts a skill, trust the tool and flag the drift.

Strong defaults

Each skill owns its own exceptions; these are the defaults.

• The Code node is a last resort. Expression first, then an arrow function inside Edit Fields, then a Code node only when neither can do the job. See n8n-code-javascript.
• A Set node feeding 0–1 consumers is almost always wrong. Inline the expression at the consumer instead. See n8n-expression-syntax.
• Per-item iteration is automatic. Don't add a Loop Over Items node to "make it loop" when default per-item execution already handles the case.
• Configure from the live schema, never from memory. get_node before you set parameters. See n8n-node-configuration.

Red flags: "about to ___" → invoke ___

If you catch yourself thinking any of these, stop and invoke the named skill first.

Skill index

n8n-mcp tools — working knowledge from turn one

Qualified names look like mcp__<server>__<tool> (<server> is usually n8n-mcp). This closes the gap where a tool's full description isn't loaded until first use.

Discovery & docs

• tools_documentation — meta-docs for every tool; {topic:"ai_agents_guide", depth:"full"} for the agent guide.
• search_nodes — find nodes by keyword.
• get_node — node info. Takes a single SHORT-form nodeType (nodes-base.httpRequest, nodes-langchain.agent), plus detail (minimal/standard/full) and mode (info/docs/search_properties/versions).
• validate_node — validate one node's config in isolation (profiles: minimal/runtime/ai-friendly/strict).
• search_templates / get_template — the template library (by keyword, nodes, task, metadata).

Build & edit

• n8n_create_workflow — create from full workflow JSON.
• n8n_update_partial_workflow — incremental diff ops ({id, operations:[…]}): addNode, updateNode, patchNodeField, addConnection, setNodeGroups, activateWorkflow, etc. Preferred for edits.
• Canvas groups (n8n 2.28+) survive your edits without being managed: a grouped node you remove is pruned from its group, and a group n8n can no longer accept is ungrouped so the edit still lands — nodes and connections untouched, every adjustment reported in details.warnings. To create or change groups, use the setNodeGroups op (full replacement; [] ungroups everything). See n8n-mcp-tools-expert.
• n8n_update_full_workflow — full replacement.
• n8n_autofix_workflow — auto-fix common issues.
• n8n_deploy_template — deploy a template to the instance.

Validate (necessary, not sufficient — always pair with the antipattern scan)

• validate_workflow — full JSON in, errors/warnings/fixes out. Node types here are LONG form (n8n-nodes-base.set).
• n8n_validate_workflow — validate a deployed workflow by {id} (no node JSON to inspect).

Inspect & lifecycle

• n8n_get_workflow — fetch a workflow (full / structure / active / filtered / minimal). Use it to verify connections after edits; mode="filtered" + nodeNames reads one heavy node (e.g. long Code source) without pulling the whole workflow, which can truncate client-side.
• n8n_list_workflows — list/filter (search before duplicating logic).
• n8n_delete_workflow, n8n_workflow_versions (history/rollback), n8n_instances (multi-instance accounts only: list/switch the target instance — see n8n-multi-instance), n8n_health_check (returns the resolved instanceName).

Test & run

• n8n_test_workflow — runs real nodes (Code, HTTP, DB writes, sends all fire). Ask the user before running when side effects exist.
• n8n_executions — list/inspect executions. There is no execute_workflow tool.
• n8n_evaluations — evaluation test runs: list runs, aggregated metrics, per-case results (n8n ≥ 2.30), plus run/cancel to start or stop a run (n8n ≥ 2.32). run executes the workflow against its whole dataset — real nodes fire, so ask the user first. A 403 can mean the API key was created before the action's minimum version (re-create it for the testRun scopes), evaluations aren't licensed on the plan, or the key's owner lacks access to the workflow — for run/cancel, specifically the workflow:execute scope.

Data, credentials, audit

• n8n_manage_datatable — Data Table CRUD, filtering, dry-run.
• n8n_manage_credentials — credential CRUD + getSchema discovery.
• n8n_audit_instance — security audit (hardcoded secrets, unauthenticated webhooks, error-handling gaps).

Node-type form trap: get_node / validate_node take SHORT form (nodes-base.set); workflow JSON inside validate_workflow / n8n_create_workflow uses LONG form (n8n-nodes-base.set). Mixing them is a common, silent mistake — see n8n-mcp-tools-expert.

The protocol, in order

1. Recognize the matching skill from the index and invoke it before the first MCP call.
2. Skim tools_documentation once per session to refresh the tool surface if you're unsure.
3. get_node before configuring any node — read the live schema, don't assume.
4. Build / edit, then validate_workflow before activating and n8n_get_workflow after to check connections.
5. Surface any drift you notice (missing tool, changed parameter, diverging behavior).

When in doubt

• Can't find a workflow the user built in the UI? The most common cause is per-workflow MCP access being off. Ask them to open it in n8n, go to Settings, and enable MCP access.
• User says it's broken? Believe them. Re-check parameters against get_node, trace data references, inspect the execution. See n8n-validation-expert.
• No skill fits and the task is non-trivial? Ask before guessing.

These are opinionated best practices, not laws. Disagree with a call? It's all markdown — edit the skill.