"Sentry" matching MCP servers:

Enables interaction with Sentry's error tracking and monitoring tools through a unified API, allowing natural language access to Sentry services.

Enables Pi to connect to Sentry's MCP endpoint, allowing an agent to search issues, events, and traces after OAuth sign-in.

A Model Context Protocol server that enables retrieving and analyzing Sentry issues, including stacktraces and debugging information.

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.

A Model Context Protocol server that retrieves and analyzes Sentry.io issues, allowing users to inspect error reports, stacktraces, and debugging information from their Sentry account.

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

Enables AI assistants to retrieve and analyze Sentry issues, including error reports, stacktraces, and debugging information from Sentry.io.

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.

Fast and minimal Sentry MCP server written in Rust

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 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.

Bridges OpenAI Codex with Sentry to automatically fetch, analyze, and fix errors using AI.

Enables interaction with Sentry's error tracking platform to fetch and manage issue details, events, and project information through the Sentry API.

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

Integrates Sentry error tracking and JIRA project management APIs, enabling users to query organizations, projects, and issues from Sentry, and retrieve or update JIRA ticket information through natural language.

Enables comprehensive Sentry monitoring including performance analysis, issue tracking, and transaction tracing.

An MCP server that connects to Sentry.io or self-hosted Sentry instances to retrieve and analyze error reports, stack traces, and debugging information.