AI Agent based Playwright MCP using credentials

Help me Build my Workflow
,
1

I’d like to ask for some help please. After hours of playing and google/chatbot/forums, I’ve coome here for help :blush:

I have a working workflow using an AI agent with OpenAI/Gemini Chat model and a Playwright MCP Tool. I am hosting my own n8n and Playwright MCP servers.

I am using it for web crawling/automation and can type requests into the chat window and the AI/Playwright MCP server can crawl / scrape web pages successfully.

I can type “Login to www.domain.com with username:MrBlobby and password:dontshare and the AI uses this just fine to login to the website.

However, I dont want to pass the credentials to the AI Chat as this feels very insecure. I have been trying and failing to find a way to save n8n credentials that I can pass on more securely.

Does anyone have any tips or code I can use to make this happen please?

This is my simple workflow:

1 „Gefällt mir“
2

Hi. Anyone have any idea how I can achieve this please?

I have looked into the getcredentials method but it seems to not be available for me to use:

async function main() {
  try {
    // Replace 'genericCredentials' with your credential type and 'WebsiteLogin' with your credential name
    const credentials = await $.getCredentials('stored-creds');
    return [{ json: { email: credentials.email, password: credentials.password } }];
  } catch (error) {
    throw new Error(`Failed to fetch credentials: ${error.message}`);
  }
}
return main();
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3

Hey can you tell me how did you get the MCP working. I am trying but unable to call as playwright mcp needs proxy for http calling. Adding MCP only supporting http streamable

5

Hey does this help at all:

I run self-hosted non-docker, test environ. my n8n does NOT have the new fancy “variables” section.

I grab env variables at n8n startup, via a bat file. I start n8n, a couple other things.
Bat file has code section like this:
set ENV_FILE=C:\Users\YOURPATH.n8n.env
:: 1. LOAD .ENV
if not exist “%ENV_FILE%” (
echo ERROR: .env not found at %ENV_FILE%
pause & exit /b 1
)
echo Loading %ENV_FILE%…
for /f “usebackq eol=# delims=” %%L in (“%ENV_FILE%”) do (
set “%%L”
)

AND i have an env var set: N8N_BLOCK_ENV_ACCESS_IN_NODE=false.

see vid - i put env var wherever i may need in a flow, and the UI complains** it says not accessible! Then it goes ahead and runs, resolves fine. Here i demonstrate a Slack message firing off to url


And heres the old thread:
http://community.n8n.io/t/no-access-to-env/20665/10

Getting a generated token
6

Your $.getCredentials idea was actually right, like you were so close.

Drop the dot — it’s $getCredentials() not $.getCredentials(), I’ve done this myself tbh. And um, you need to create a Generic Credential in n8n’s credential store first, the name you pass in has to match it exactly.

So like this:

const creds = await $getCredentials('MyWebsiteLogin');
return [{ json: { username: creds.username, password: creds.password } }];

Stick that in a Code node before your AI Agent, then in the system prompt just reference it:

When logging into domain.com use username: {{ $('Code').item.json.username }} 
and password: {{ $('Code').item.json.password }}

Credentials stay encrypted in n8n, never touch the chat. Does exactly what you wanted.

Oh and if you’re on a recent version of n8n there’s an even easier way — Settings > Variables, add them there and just use {{ $vars.SITE_USERNAME }} anywhere in the workflow, no code node needed at all.

The env variable thing mentioned above works but it’s a bit of a faff honestly.

7

Ich würde bei dem letzten Schritt vorsichtig sein. Selbst wenn das Geheimnis in n8n gespeichert ist, wird durch die Interpolation von Benutzername/Passwort in den Agent-Prompt das Geheimnis trotzdem in den Modellkontext eingefügt.

Sicherer Ansatz: Ein kleines Login-Tool besitzt die Anmeldedaten, führt die Anmeldung durch und gibt nur Status, Domain, Kontobezeichnung und Sitzungsstatus zurück. Der Agent erhält eine Bestätigung, nicht das Passwort.

8

Der Schlüssel ist, Anmeldedaten vor der KI-Schicht aufzulösen, nicht innerhalb dieser. Fügen Sie einen Code-Node vor Ihrem KI-Agent hinzu, der $getCredentials('your-cred-name') aufruft – das funktioniert im Code-Node-Kontext einwandfrei, auch wenn es in Tool-Sub-Workflows nicht verfügbar ist. Übergeben Sie dann die aufgelösten Werte in das System-Message-Feld des KI-Agents, indem Sie einen Ausdruck wie {{ $('Code').item.json.username }} verwenden. Das LLM erhält bereits aufgelöste Werte im Kontext und sieht niemals rohe Anmeldedaten im Chat-Verlauf.

Wenn $getCredentials in Ihrem Setup blockiert ist, ist eine zuverlässige Alternative, Anmeldedaten als n8n-Umgebungsvariablen zu speichern und sie mit {{ $env.MY_PASSWORD }} in der System-Eingabeaufforderung zu referenzieren. Das Playwright-MCP-Tool erhält sie dann als Teil der Task-Anweisungen, ohne sie im Konversationsverlauf offenzulegen.