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Overview

MCP-use includes an opt-out telemetry system that helps us understand how the library is being used in practice. This data enables us to:
  • Prioritize development based on real usage patterns
  • Optimize performance for common workflows
  • Improve compatibility with popular model providers
  • Focus on the most valuable features
Privacy First: All telemetry is anonymized and can be completely disabled with a single environment variable.

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What We Collect

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Agent Execution Data

When you use MCPAgent.run() or MCPAgent.astream(), we collect:
  • Query and response content (to understand use cases)
  • Model provider and name (e.g., “openai”, “gpt-4”)
  • MCP servers connected (types and count, not specific URLs/paths)
  • Tools used (which MCP tools are popular)
  • Performance metrics (execution time, steps taken)
  • Configuration settings (memory enabled, max steps, etc.)

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System Information

  • Package version (for version adoption tracking)
  • Error types (for debugging and improvement)
  • Package download analytics (via Scarf for distribution insights)

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What We DON’T Collect

  • Personal information (no names, emails, or identifiers)
  • Server URLs or file paths (only connection types)
  • API keys or credentials (never transmitted)
  • IP addresses (PostHog configured with disable_geoip=False)

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How to Disable Telemetry

export MCP_USE_ANONYMIZED_TELEMETRY=false

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In Your Code

import os
os.environ["MCP_USE_ANONYMIZED_TELEMETRY"] = "false"

# Now use MCP-use normally - no telemetry will be collected
from mcp_use import MCPAgent

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Verification

When telemetry is disabled, you’ll see this debug message: 
DEBUG: Telemetry disabled
When enabled, you’ll see: 
INFO: Anonymized telemetry enabled. Set MCP_USE_ANONYMIZED_TELEMETRY=false to disable.

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Data Storage and Privacy

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Anonymous User IDs

  • A random UUID is generated and stored locally in your cache directory
  • Linux/Unix: ~/.cache/mcp_use/telemetry_user_id
  • macOS: ~/Library/Caches/mcp_use/telemetry_user_id
  • Windows: %LOCALAPPDATA%\mcp_use\telemetry_user_id

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Data Transmission

  • Data is sent to both PostHog (EU servers: https://eu.i.posthog.com) and Scarf (https://mcpuse.gateway.scarf.sh/simple/)
  • No personal information is ever transmitted
  • Data is used only for aggregate analysis and package usage analytics

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Example Telemetry Event

Here’s what a typical telemetry event looks like: 
{
  "event": "mcp_agent_execution",
  "distinct_id": "550e8400-e29b-41d4-a716-446655440000",
  "properties": {
    "mcp_use_version": "1.3.0",
    "execution_method": "run",
    "query": "Help me analyze sales data from the CSV file",
    "response": "I'll help you analyze the sales data...",
    "model_provider": "openai",
    "model_name": "gpt-4",
    "server_count": 2,
    "server_identifiers": [
      {"type": "stdio", "command": "python -m server"},
      {"type": "http", "base_url": "localhost:8080"}
    ],
    "tools_used_names": ["read_file", "analyze_data"],
    "execution_time_ms": 2500,
    "success": true
  }
}

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Benefits to the Community

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For Users

  • Better library through data-driven improvements
  • Faster issue resolution via error pattern detection
  • Feature prioritization based on actual usage

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For Developers

  • Compatibility insights for new model providers
  • Performance optimization targets
  • Usage pattern understanding for better APIs

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Technical Implementation

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Clean Architecture

The telemetry system uses a decorator pattern that ensures:
  • Zero overhead when disabled
  • No exceptions if PostHog or Scarf services are unavailable
  • Graceful degradation in all failure scenarios
  • Dual telemetry to both PostHog and Scarf for comprehensive analytics

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Code Example

# This is how telemetry works internally:
@requires_telemetry
def track_agent_execution(self, ...):
    # This method only executes if telemetry is enabled
    # If disabled, it returns None immediately
    pass

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Frequently Asked Questions

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Can I see what data is being sent?

Yes! Set your logging level to DEBUG to see telemetry events: 
import logging
logging.basicConfig(level=logging.DEBUG)

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Does telemetry affect performance?

  • When disabled: Zero performance impact
  • When enabled: Minimal impact (async data transmission)

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Can I opt out after using the library?

Yes! Set the environment variable and restart your application. You can also delete the user ID file to reset your anonymous identifier.

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Is this GDPR compliant?

Yes. The telemetry system:
  • Collects no personal data
  • Uses anonymous identifiers
  • Provides easy opt-out
  • Processes data for legitimate business interests (software improvement)

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Support

If you have questions about telemetry:
  • Disable it: Use MCP_USE_ANONYMIZED_TELEMETRY=false
  • Report issues: GitHub Issues
  • Check logs: Enable DEBUG logging to see telemetry activity
Remember: Telemetry helps us build a better library for everyone, but your privacy comes first. We’ve designed the system to be transparent, minimal, and easily disabled.