Overview
n8n-MCP collects anonymous usage statistics to help improve the tool. This data collection is designed to respect user privacy while providing valuable insights into how the tool is used.All telemetry is optional and can be disabled at any time. See the Opt-Out section below.
What We Collect
We collect the following anonymous data:Anonymous User ID
Anonymous User ID
A hashed identifier derived from your machine characteristics. No personal information is included in this hash.
Tool Usage
Tool Usage
- Which MCP tools are used
- Performance metrics (execution time, success/failure)
- Frequency of tool invocations
Workflow Patterns
Workflow Patterns
- Sanitized workflow structures (all sensitive data removed)
- Node type usage patterns
- Workflow complexity metrics
Error Types
Error Types
- Categories of errors encountered
- No error messages with user data
- Stack trace patterns (sanitized)
System Information
System Information
- Platform (Linux, macOS, Windows)
- Architecture (x64, arm64)
- Node.js version
- n8n-MCP version
What We DON’T Collect
- ❌ Personal information or usernames
- ❌ API keys, tokens, or credentials
- ❌ URLs, endpoints, or hostnames
- ❌ Email addresses or contact information
- ❌ File paths or directory structures
- ❌ Actual workflow data or parameters
- ❌ Database connection strings
- ❌ Any authentication information
Data Sanitization
All collected data undergoes automatic sanitization:Data Storage
Secure Storage
Data is stored securely using Supabase with encryption
Write-Only Access
Anonymous users have write-only access (cannot read data back)
Row Level Security
RLS policies prevent data access by anonymous users
No Personal Data
No personal identification is possible from collected data
Opt-Out
You can disable telemetry at any time:- npx Users
- Docker Users
- docker-compose
Data Usage
Collected data is used solely to:Feature Usage
Understand which features are most used
Error Patterns
Identify common error patterns
Performance
Improve tool performance and reliability
Development Priorities
Guide development priorities
Machine Learning
All ML training uses sanitized, anonymized data only.
- Workflow generation suggestions
- Common pattern detection
- Error prediction and prevention
npx n8n-mcp telemetry disable.
Data Retention
- Data is retained for analysis purposes
- No time-based deletion policy (data is already anonymized)
- No personal identification is possible from the collected data
Privacy Commitment
Our Promise
We are committed to:
- Collecting only anonymous, sanitized data
- Providing easy opt-out mechanisms
- Being transparent about data usage
- Never selling or sharing user data
- Continuously improving privacy protections
Changes to This Policy
We may update this privacy policy from time to time. Updates will be reflected in this document. Last updated: 2025-11-06Contact
For questions about telemetry or privacy, please:GitHub Issues
Open an issue on GitHub
Contact the maintainer directly