"Sentry" matching MCP servers:

A remote Model Context Protocol server acting as middleware to the Sentry API, allowing AI assistants like Claude to access Sentry data and functionality through natural language interfaces.

Automatically reads Sentry issues, investigates them by analyzing your Ruby codebase, explains why issues happened, and provides fix suggestions.

Enables interaction with Sentry organizations, projects, and issues directly from MCP clients like Claude Code.

Enables searching and analyzing Sentry issues, events, and traces via natural language, providing tools for error investigation and distributed tracing.

MCP server for self-hosted Sentry instances, providing tools to query and triage issues and events, inspect stack frames, manage releases, and access raw Sentry API.

A Model Context Protocol server that lets AI assistants interact with the Sentry API to retrieve and analyze error data, manage projects, and monitor application performance.

A Model Context Protocol server that enables AI assistants to interact with Sentry for error tracking and monitoring, allowing retrieval and analysis of error data, project management, and performance monitoring through the Sentry API.

Integrates Sentry error monitoring with AI-powered analysis to automatically capture frontend JavaScript errors and provide intelligent repair suggestions through multiple AI models including OpenAI, Claude, and Gemini.

Enables querying and managing Sentry projects, issues, and events through natural language.

A stateless FastMCP server that enables interaction with multiple Sentry instances, including US, EU, and self-hosted versions, through a single deployment. It provides tools for searching issues, events, and traces, allowing users to monitor and debug applications using natural language.

A TypeScript server that allows AI agents to access, retrieve, and analyze Sentry error data through the Modern Context Protocol.

A TypeScript implementation of a Model Context Protocol server that connects to Sentry error tracking service, allowing AI models to query and analyze error reports and events.

This server provides tools to inspect error reports, stacktraces, and other debugging information from your Sentry account.

MCP server for integrating self-hosted Sentry with AI assistants, enabling project and issue listing, issue details with stack traces, and event retrieval.

Enables tracing mcp-use tool callbacks and capturing tool errors and exceptions in Sentry via MCP middleware, without SDK changes or additional services.

A curated collection of Model Context Protocol (MCP) servers for popular SaaS platforms — Stripe, Sentry, Notion, Linear, Datadog, Vercel, PagerDuty, HubSpot, Intercom, Shopify, Google Workspace

Connects AI agents to live observability stacks including Sentry, GitHub, Vercel, Better Stack, and Cloudflare, enabling end-to-end incident investigation, deployment correlation, root cause analysis, and regression triage.

Enables AI agents to read realistic, coherent data—repos, pull requests, issues, commits, users—through API-compatible, read-only replicas of 21 developer platforms including GitHub, Jira, Linear, Slack, Sentry and Salesforce, all preloaded with one simulated company so integrations can be built and tested with no accounts, credentials, rate-limit worry, or cleanup.

MCP server for monitoring, diagnosing, and auto-correcting observability issues across platform services, integrating with Sentry and PostgreSQL for error tracking and billing pipeline health.

MCP server that exposes the AHDB RB209 Nutrient Management Guide Web API v2 as tools, enabling nutrient planning and access to all 97 endpoints.