MCP Sentry Server

v1.0.0

Sentry

MCPerror-trackingmonitoringmcpmodel-context-protocol
79
Strong
About This MCP

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.

Last Evaluated: November 8, 2025
Official Website

Trust Vector Analysis

Dimension Breakdown

🚀Performance & Reliability
+
error query reliability

Query success rate testing

Evidence
Sentry API — Highly reliable error and issue querying
highVerified: 2025-11-08
stack trace parsing accuracy

Parsing accuracy testing

Evidence
Sentry Stack Traces — Accurate stack trace parsing and symbolication
highVerified: 2025-11-08
real time monitoring

Real-time monitoring testing

Evidence
Sentry Webhooks — Real-time error notifications via webhooks
highVerified: 2025-11-08
rate limit handling

Rate limiting behavior testing

Evidence
Sentry API Rate Limits — Subject to API rate limits with retry-after headers
mediumVerified: 2025-11-08
error recovery

Error handling testing

Evidence
Implementation Review — Handles API errors with retry logic
mediumVerified: 2025-11-08
🛡️Security
+
authentication security

Authentication mechanism review

Evidence
Sentry Authentication — Uses auth tokens or integration tokens with scoped permissions
highVerified: 2025-11-08
token exposure risk

Token security analysis

Evidence
MCP Security Model — Sentry auth token stored locally; AI can access error data
highVerified: 2025-11-08
source code exposure risk

Code exposure assessment

Evidence
Security Analysis — Stack traces may contain source code snippets and file paths
highVerified: 2025-11-08
issue modification control

Modification control testing

Evidence
Sentry API — Can update issue status and assign issues within permissions
mediumVerified: 2025-11-08
organization access control

Access control testing

Evidence
Sentry Permissions — Respects Sentry organization and project permissions
highVerified: 2025-11-08
audit logging

Audit logging review

Evidence
Sentry Audit Log — Comprehensive audit logging for all operations
highVerified: 2025-11-08
🔒Privacy & Compliance
+
error data exposure

Data flow analysis

Evidence
MCP Data Flow — Error messages, stack traces, and context data sent to LLM provider
highVerified: 2025-11-08
user data in errors

PII exposure assessment

Evidence
Privacy Analysis — Error context may include user IDs, emails, and session data
highVerified: 2025-11-08
source code privacy

Code privacy assessment

Evidence
Stack Traces — Stack traces contain file paths and code snippets
highVerified: 2025-11-08
third party data sharing

Data sharing analysis

Evidence
LLM Provider Policies — Error and monitoring data shared with LLM provider
highVerified: 2025-11-08
breadcrumb data privacy

Breadcrumb privacy assessment

Evidence
Sentry Breadcrumbs — Breadcrumbs may contain sensitive user actions and data
mediumVerified: 2025-11-08
👁️Trust & Transparency
+
documentation quality

Documentation completeness review

Evidence
Sentry MCP Docs — Comprehensive documentation from official Sentry team
highVerified: 2025-11-08
operation visibility

Logging and traceability assessment

Evidence
Sentry Audit Log — All API operations logged in Sentry audit log and MCP logs
highVerified: 2025-11-08
open source transparency

Source code review

Evidence
GitHub Repository — Open source implementation from Sentry
highVerified: 2025-11-08
api coverage clarity

API documentation review

Evidence
MCP Server Documentation — Clear documentation of supported Sentry operations
mediumVerified: 2025-11-08
⚙️Operational Excellence
+
ease of setup

Setup complexity assessment

Evidence
Setup Documentation — Simple setup requiring Sentry auth token
highVerified: 2025-11-08
api performance

Performance benchmarking

Evidence
Sentry API Performance — Fast API responses (typically 100-500ms)
highVerified: 2025-11-08
reliability

Reliability analysis

Evidence
Sentry Infrastructure — Built on highly reliable Sentry infrastructure with 99.9%+ uptime
highVerified: 2025-11-08
operation coverage

Feature coverage assessment

Evidence
Sentry MCP Server — Covers errors, issues, releases, performance, and projects
highVerified: 2025-11-08
official support

Maintainer support assessment

Evidence
Sentry Team — Officially maintained by Sentry with active support
highVerified: 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

Excellent for AI-assisted debugging and error resolution

customer support

Good for analyzing customer-reported errors and incidents

content creation

Limited applicability for content workflows

data analysis

Excellent for error analytics, trend analysis, and performance monitoring

research assistant

Useful for researching error patterns and debugging strategies

legal compliance

Risk of exposing application internals and user data in errors

healthcare

High risk of exposing PHI in error context and logs

financial analysis

Moderate risk of financial data in error messages

education

Good for teaching debugging and error handling

creative writing

Low relevance to creative writing workflows