MCP Sentry Server
Sentry
79·Strong
Overall Trust Score
Official Sentry MCP server for error tracking and monitoring integration. Enables AI models to query errors, analyze stack traces, manage issues, track releases, and access performance data. Essential for AI-powered debugging, incident response, and application monitoring workflows.
error-tracking
monitoring
mcp
model-context-protocol
Trust Vector
Performance & Reliability
87
error query reliability92
error query reliability
92
Methodology
Query success rate testing
Evidence
Confidence: highLast verified: 2025-11-08
stack trace parsing accuracy90
stack trace parsing accuracy
90
Methodology
Parsing accuracy testing
Evidence
Confidence: highLast verified: 2025-11-08
real time monitoring88
real time monitoring
88
Methodology
Real-time monitoring testing
Evidence
Confidence: highLast verified: 2025-11-08
rate limit handling82
rate limit handling
82
Methodology
Rate limiting behavior testing
Evidence
Confidence: mediumLast verified: 2025-11-08
error recovery85
error recovery
85
Methodology
Error handling testing
Evidence
Confidence: mediumLast verified: 2025-11-08
Security
72
authentication security85
authentication security
85
Methodology
Authentication mechanism review
Evidence
Confidence: highLast verified: 2025-11-08
token exposure risk65
token exposure risk
65
Methodology
Token security analysis
Evidence
Confidence: highLast verified: 2025-11-08
source code exposure risk60
source code exposure risk
60
Methodology
Code exposure assessment
Evidence
Confidence: highLast verified: 2025-11-08
issue modification control75
issue modification control
75
Methodology
Modification control testing
Evidence
Confidence: mediumLast verified: 2025-11-08
organization access control78
organization access control
78
Methodology
Access control testing
Evidence
Confidence: highLast verified: 2025-11-08
audit logging85
audit logging
85
Methodology
Audit logging review
Evidence
Confidence: highLast verified: 2025-11-08
Privacy & Compliance
66
error data exposure62
error data exposure
62
Methodology
Data flow analysis
Evidence
Confidence: highLast verified: 2025-11-08
user data in errors58
user data in errors
58
Methodology
PII exposure assessment
Evidence
Confidence: highLast verified: 2025-11-08
source code privacy65
source code privacy
65
Methodology
Code privacy assessment
Evidence
Confidence: highLast verified: 2025-11-08
third party data sharing68
third party data sharing
68
Methodology
Data sharing analysis
Evidence
Confidence: highLast verified: 2025-11-08
breadcrumb data privacy70
breadcrumb data privacy
70
Methodology
Breadcrumb privacy assessment
Evidence
Confidence: mediumLast verified: 2025-11-08
Trust & Transparency
84
documentation quality88
documentation quality
88
Methodology
Documentation completeness review
Evidence
Confidence: highLast verified: 2025-11-08
operation visibility85
operation visibility
85
Methodology
Logging and traceability assessment
Evidence
Confidence: highLast verified: 2025-11-08
open source transparency90
open source transparency
90
Methodology
Source code review
Evidence
Confidence: highLast verified: 2025-11-08
api coverage clarity73
api coverage clarity
73
Methodology
API documentation review
Evidence
Confidence: mediumLast verified: 2025-11-08
Operational Excellence
85
ease of setup85
ease of setup
85
Methodology
Setup complexity assessment
Evidence
Confidence: highLast verified: 2025-11-08
api performance85
api performance
85
Methodology
Performance benchmarking
Evidence
Confidence: highLast verified: 2025-11-08
reliability90
reliability
90
Methodology
Reliability analysis
Evidence
Sentry Infrastructure
Built on highly reliable Sentry infrastructure with 99.9%+ uptime
Date: 2025-11-16
Confidence: highLast verified: 2025-11-08
operation coverage82
operation coverage
82
Methodology
Feature coverage assessment
Evidence
Confidence: highLast verified: 2025-11-08
official support88
official support
88
Methodology
Maintainer support assessment
Evidence
Confidence: highLast verified: 2025-11-08
✨ Strengths
- •Comprehensive error tracking and monitoring capabilities
- •Official Sentry implementation with active support
- •Accurate stack trace parsing and symbolication
- •Real-time error notifications via webhooks
- •Excellent for AI-powered debugging and incident response
- •Comprehensive audit logging for all operations
⚠️ Limitations
- •Error messages and stack traces exposed to LLM provider
- •Error context may include user IDs, emails, and session data
- •Stack traces contain source code snippets and file paths
- •Breadcrumbs may contain sensitive user actions
- •Subject to Sentry API rate limits
- •Requires careful data scrubbing configuration to avoid PII exposure
📊 Metadata
license: MIT
supported platforms:
0: All platforms with Node.js/Python
programming languages:
0: TypeScript
1: Python
mcp version: 1.0
github repo: https://github.com/getsentry/sentry-mcp-server
api dependency: Sentry REST API
authentication: Sentry Auth Token or Integration Token
first release: 2024-11
maintained by: Sentry
Use Case Ratings
code generation
85
Excellent for AI-assisted debugging and error resolution
customer support
80
Good for analyzing customer-reported errors and incidents
content creation
55
Limited applicability for content workflows
data analysis
92
Excellent for error analytics, trend analysis, and performance monitoring
research assistant
72
Useful for researching error patterns and debugging strategies
legal compliance
58
Risk of exposing application internals and user data in errors
healthcare
52
High risk of exposing PHI in error context and logs
financial analysis
60
Moderate risk of financial data in error messages
education
82
Good for teaching debugging and error handling
creative writing
45
Low relevance to creative writing workflows