mcp-n8n-ops
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-n8n-opsCheck if any workflows are failing right now"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-n8n-ops
An MCP server for operating an n8n instance. Ask an AI assistant what is failing, why, and since when — instead of clicking through the executions list.
You: Anything broken in n8n today?
Assistant: (calls
failing_workflows) Two workflows are failing. "Invoice sync" has 14 failures since yesterday 09:40, allECONNREFUSED talking to Google Sheets. "Cart recovery" failed twice, both rate limits. The Sheets one looks like a credential or network problem, not a logic bug — the failures start abruptly and share one error.
Read-only by default. Tools that change state are not merely refused —
they are absent from the tool list unless you start the server with
--allow-write. A model cannot be talked into calling a tool it cannot see.
Zero dependencies. The MCP stdio transport is implemented directly, so this runs on any Python 3.9+ with nothing installed — which is what you want for a tool you drop onto the box next to n8n.
Install
pip install git+https://github.com/Redsf/mcp-n8n-opsNot on PyPI yet, so install from git.
Configure
Get an API key from n8n: Settings → n8n API → Create an API key.
Claude Desktop / Claude Code
{
"mcpServers": {
"n8n-ops": {
"command": "mcp-n8n-ops",
"env": {
"N8N_URL": "https://n8n.example.com",
"N8N_API_KEY": "n8n_api_..."
}
}
}
}Add "args": ["--allow-write"] only if you want the assistant able to activate
and deactivate workflows. Read the safety section first.
Any other MCP client
It speaks MCP over stdio:
N8N_URL=https://n8n.example.com N8N_API_KEY=n8n_api_... mcp-n8n-opsTools
Read (always available)
Tool | Answers |
| Start here. Which workflows are failing, ranked by failure count, each with a sample error and the time of the last failure. |
| Instance overview: workflow count, how many active, recent error rate. |
| Recent executions, filterable by status or workflow. |
| One execution, including the actual error message. |
| Workflows with id, name, active state, node count, tags. |
| One workflow's summary, optionally its node list. |
Write (only with --allow-write)
Tool | Does |
| Activates or deactivates a workflow. |
There is deliberately no delete tool, and none is planned. Deleting a workflow or an execution is not something an assistant should be able to do on your behalf, whatever the flag says.
Aggregation happens server-side
failing_workflows returns a small ranked answer, not 200 raw executions for
the model to tally:
{
"failed_executions_examined": 16,
"distinct_workflows_failing": 2,
"workflows": [
{
"workflow_id": "1",
"workflow_name": "Invoice sync",
"failures": 14,
"last_failure": "2026-07-21T10:00:00Z",
"sample_error": "ECONNREFUSED talking to Google Sheets"
}
]
}Counting in Python instead of in the model is faster, cheaper, and it does not get the arithmetic wrong.
Safety
This server is driven by a model, which changes what "safe defaults" means.
Read-only unless you opt in. Write tools are hidden, not just blocked. Asked for anyway, the server explains why rather than returning a bare "unknown tool", so nobody wastes time hunting a typo.
No delete, at any privilege level.
The API key is never returned. It goes out in a header and never appears in a tool result or an error message.
n8n failures are tool errors, not crashes. An unreachable instance or a bad key comes back as
isErrorwith a readable message, and the server keeps serving. A dead n8n should not take down the assistant's session.stdout carries protocol only. All logging goes to stderr. Writing anything else to stdout corrupts the JSON-RPC stream — the most common way a hand-written MCP server breaks.
A read-only key is still a broad grant: it can read every workflow, including node parameters. Give this server its own key, and revoke it when you are done.
Verifying it works
The test suite drives the real protocol — handshake, notification handling, malformed frames, tool dispatch — against a fake n8n, so it runs with no instance and no network:
pip install -e ".[dev]"
pytestCI additionally starts the compiled entry point as a subprocess against a stub n8n HTTP server and drives it with real MCP messages over stdio, asserting the handshake, the tool list, an aggregated diagnosis, and that a write tool is refused in read-only mode.
Why not the official MCP SDK?
The SDK requires Python 3.10+. This targets 3.9 so it runs on the long-lived
boxes n8n tends to live on, and stays dependency-free so pip install cannot
drag in a transitive CVE on a machine that has production credentials on it.
MCP's stdio transport is newline-delimited JSON-RPC 2.0 — small enough to
implement correctly and test exhaustively, which is what the suite does.
Related
n8n-workflow-linter — catch problems before deploy
agent-evals — check behaviour before users do
automation-roi-toolkit — decide what to build
same-system-three-ways — n8n vs Python vs TypeScript, measured
License
MIT — see LICENSE.
This server cannot be installed
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