@sentry/mcp-server
MCP ServerFreeSentry MCP Server
Capabilities10 decomposed
sentry error event retrieval and filtering via mcp
Medium confidenceExposes Sentry's error event API through the Model Context Protocol, allowing LLM agents to query and filter error events by project, environment, release, and time range. Implements MCP resource and tool patterns to translate natural language queries into Sentry API calls, returning structured event data with stack traces, breadcrumbs, and user context for analysis and debugging.
Implements MCP server pattern to expose Sentry's REST API as native LLM tools, enabling agents to query production errors without custom API wrapper code. Uses MCP's resource and tool abstractions to translate between natural language queries and Sentry's filter syntax.
Provides direct LLM access to Sentry data via standard MCP protocol, eliminating the need for custom API clients or webhook integrations that other error-tracking tools require
sentry issue lifecycle management via mcp tools
Medium confidenceExposes Sentry issue operations (resolve, ignore, assign, update status) as MCP tools callable by LLM agents. Translates agent actions into Sentry API mutations, enabling automated issue triage, assignment, and status updates based on error analysis. Implements idempotent operations with proper error handling for concurrent modifications.
Wraps Sentry's issue mutation APIs as composable MCP tools, allowing LLM agents to perform multi-step triage workflows (analyze error → assign → resolve) without context switching or manual intervention. Implements proper error handling for race conditions when multiple agents or users modify issues concurrently.
Enables fully automated issue management workflows through LLM agents, whereas webhook-based alternatives require custom backend logic to translate events into actions
sentry project and organization context provisioning
Medium confidenceProvides MCP resources that expose Sentry project metadata, team structure, and organization configuration to LLM agents. Implements resource listing and hierarchical navigation (organization → projects → teams) to give agents awareness of available projects, their settings, and team ownership. Caches metadata to reduce API calls during multi-step workflows.
Implements MCP resource pattern to expose Sentry's hierarchical organization structure (org → projects → teams) as navigable context, allowing agents to understand project ownership and scope queries appropriately. Uses caching to minimize API calls while maintaining freshness.
Provides structured, hierarchical access to organization metadata through MCP resources, whereas direct API clients require agents to manually construct queries and parse nested responses
natural language to sentry query translation
Medium confidenceTranslates natural language queries from LLM agents into Sentry's filter syntax and API parameters. Implements semantic understanding of error attributes (environment, release, user, error type) and maps them to Sentry's query language. Handles ambiguous queries by providing clarification options or reasonable defaults.
Leverages the LLM's semantic understanding to translate natural language into Sentry's filter syntax, avoiding the need for users to learn Sentry's query language. Implemented as a tool that the LLM calls before executing actual Sentry queries.
Enables non-technical users to query error data through natural language, whereas traditional Sentry UI and API require learning filter syntax or writing custom code
error pattern detection and correlation across projects
Medium confidenceAnalyzes error events from multiple Sentry projects to identify common patterns, root causes, and correlated failures. Implements statistical analysis of error fingerprints, stack traces, and metadata to group related errors and detect systemic issues. Provides insights into error trends and impact across the organization.
Implements cross-project error correlation by aggregating events from multiple Sentry projects and applying statistical analysis to identify patterns and root causes. Uses fingerprinting and stack trace similarity to group related errors across service boundaries.
Provides automated error correlation across projects without requiring custom ETL pipelines or external analytics tools, enabling agents to discover systemic issues automatically
release and deployment context integration
Medium confidenceIntegrates Sentry release data with deployment information to correlate errors with specific code changes and deployments. Implements release-aware error filtering and analysis, allowing agents to understand which errors were introduced in which release and which deployments are affected. Supports linking errors to commits and pull requests.
Correlates Sentry error data with release and deployment metadata to provide deployment-aware error analysis. Implements release-scoped queries and trend analysis to help agents understand the impact of specific deployments.
Enables automated deployment validation and rollback decisions by correlating errors with specific releases, whereas manual approaches require developers to manually check Sentry after each deployment
performance monitoring and transaction analysis
Medium confidenceExposes Sentry's performance monitoring data (transactions, spans, latency metrics) through MCP tools, allowing agents to analyze application performance alongside error data. Implements transaction filtering, span analysis, and performance trend detection. Correlates performance degradation with errors to identify performance-related root causes.
Integrates Sentry's performance monitoring data with error analysis, allowing agents to correlate performance degradation with errors and identify performance-related root causes. Implements transaction and span filtering for detailed performance analysis.
Provides unified error and performance analysis through a single MCP interface, whereas separate error tracking and APM tools require context switching and manual correlation
user impact and session replay context
Medium confidenceExposes Sentry's user impact data and session replay information through MCP, allowing agents to understand which users are affected by errors and access session context for debugging. Implements user filtering, session correlation, and impact metrics. Provides links to session replays for visual debugging.
Correlates error data with user impact metrics and session replay information, providing agents with both quantitative impact data and qualitative debugging context. Implements user-centric error analysis rather than just technical metrics.
Enables user-impact-driven error prioritization and visual debugging through session replays, whereas error-only tracking tools lack user context and require separate session replay tools
alert rule configuration and notification management
Medium confidenceExposes Sentry's alert rules and notification settings through MCP, allowing agents to configure alerts, manage notification channels, and adjust alerting thresholds. Implements alert rule creation, modification, and testing. Supports multiple notification channels (email, Slack, PagerDuty, webhooks).
Enables programmatic alert rule management through MCP, allowing agents to create and adjust alerts based on error patterns and trends. Implements alert rule testing to validate configurations before deployment.
Provides automated alert configuration without manual UI interaction, whereas manual alert setup requires developers to navigate Sentry's UI for each rule
integration with external incident management systems
Medium confidenceIntegrates Sentry error data with external incident management platforms (PagerDuty, Opsgenie, etc.) through MCP, enabling agents to create incidents, update severity, and manage escalations based on error analysis. Implements bidirectional sync of incident status and error resolution.
Bridges Sentry error data with external incident management systems through MCP, enabling end-to-end automated incident response workflows. Implements bidirectional sync to keep error and incident status in sync.
Enables fully automated incident creation and management based on error analysis, whereas webhook-based integrations require custom backend logic to translate errors into incidents
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
Related Artifactssharing capabilities
Artifacts that share capabilities with @sentry/mcp-server, ranked by overlap. Discovered automatically through the match graph.
@sentry/mcp-server
Sentry MCP Server
Sentry
** - Retrieving and analyzing issues from Sentry.io.
Sentry MCP Server
Query Sentry issues, errors, and stack traces via MCP.
Hello from Sentry
Provide a simple MCP server implementation to demonstrate integration with Sentry. Enable developers to quickly start with MCP by offering a minimal example that can be extended for custom use cases.
Hello from Sentry
Provide a simple MCP server implementation to demonstrate integration with Sentry. Enable developers to quickly start using MCP with error monitoring and logging capabilities. Facilitate rapid development and debugging of MCP-based applications.
sentryfrogg-mcp
MCP server: sentryfrogg-mcp
Best For
- ✓DevOps engineers building AI-assisted incident response systems
- ✓Development teams automating error triage and analysis workflows
- ✓LLM agent builders needing real-time error context from production systems
- ✓Automated incident response systems that need to close issues programmatically
- ✓AI-powered triage workflows that assign errors to on-call engineers
- ✓Teams using LLM agents to manage error backlogs at scale
- ✓Multi-project organizations needing context-aware error analysis
- ✓Teams automating cross-project error correlation and analysis
Known Limitations
- ⚠Requires valid Sentry authentication token with appropriate project permissions
- ⚠Query latency depends on Sentry API response times and event volume
- ⚠Limited to events available in Sentry's retention window (varies by plan)
- ⚠No built-in caching — repeated queries hit Sentry API directly
- ⚠Requires write permissions on Sentry projects — token must have appropriate scopes
- ⚠No transaction support — multiple operations are not atomic
Requirements
Input / Output
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Sentry MCP Server
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