n8n Advisor
Provides tools for reviewing and monitoring n8n workflow status, including active/inactive counts and workflows with errors.
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., "@n8n Advisorcheck workflow status in my n8n instance"
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.
n8n Advisor
MCP server for n8n workflow management. Provides AI assistants with the ability to review workflow status in n8n instances.
Features
check_workflows: Reviews all workflows and reports their status, including active/inactive counts and workflows with recent errors.
Related MCP server: Cursor n8n Builder
Installation
pip install m2ai-mcp-n8n-advisorConfiguration
Create a .env file or set environment variables:
# Base URL of your n8n instance (no trailing slash)
N8N_BASE_URL=https://your-n8n-instance.app.n8n.cloud
# API key from n8n Settings > API
N8N_API_KEY=your_api_key_hereGetting Your n8n API Key
Open your n8n instance
Go to Settings > API
Create a new API key or copy an existing one
Use the full URL of your n8n instance for
N8N_BASE_URL
Usage
Claude Desktop Configuration
Add to your claude_desktop_config.json:
{
"mcpServers": {
"n8n": {
"command": "n8n-advisor",
"env": {
"N8N_BASE_URL": "https://your-n8n-instance.app.n8n.cloud",
"N8N_API_KEY": "your_api_key_here"
}
}
}
}Or run directly with Python:
{
"mcpServers": {
"n8n": {
"command": "python",
"args": ["-m", "n8n_mcp.server"],
"env": {
"N8N_BASE_URL": "https://your-n8n-instance.app.n8n.cloud",
"N8N_API_KEY": "your_api_key_here"
}
}
}
}Available Tools
check_workflows
Reviews all workflows and reports their status.
Parameters: None
Returns:
total_workflows: Total number of workflowsactive_workflows: Number of active workflowsinactive_workflows: Number of inactive workflowsworkflows_with_errors: Count of workflows with recent errorserror_workflows: List of workflows with errors (id, name, error count)workflows: Detailed list of all workflows with execution stats
Example Response:
{
"total_workflows": 5,
"active_workflows": 3,
"inactive_workflows": 2,
"workflows_with_errors": 1,
"error_workflows": [
{"id": "2", "name": "Data Sync", "errors": 3}
],
"workflows": [
{
"id": "1",
"name": "Email Notifications",
"active": true,
"recent_executions": {
"success": 10,
"error": 0,
"waiting": 0,
"running": 0
}
}
]
}Development
# Install dev dependencies
pip install -e ".[dev]"
# Run tests
pytest
# Run tests with coverage
pytest --cov=n8n_mcp
# Type checking
mypy src/
# Linting
ruff check src/License
MIT
Maintenance
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