Automate workflows and connect AI agents to Sentry. Metorial is built for developers. Handling OAuth, compliance, observability, and more.
The Sentry integration lets you query error and performance data, manage issues, and retrieve project information directly from your Sentry organization, enabling faster debugging and incident response workflows.
Metorial has 600+ integrations available. Here are some related ones you might find interesting.
The Exa integration lets you perform semantic searches across the web and retrieve high-quality content directly within your workflows, enabling AI agents to find and access relevant information from billions of web pages in real-time.
The Hackernews integration lets you fetch and analyze stories, comments, and user data from Hacker News directly within your workflow, enabling you to track trending topics, monitor discussions, and gather insights from the tech community.
The Slack integration lets you read channels, send messages, and search conversations directly from your AI assistant, enabling seamless team communication and information retrieval without leaving your workflow.
The Supabase integration lets you query and manipulate your database tables, manage authentication, and interact with storage buckets directly from your AI assistant. Use it to build applications, analyze data, or automate database operations without leaving your workflow.
The Google Calendar integration lets you view, create, update, and manage calendar events directly from your workflow, enabling seamless scheduling and calendar management without switching applications.
The GitHub integration lets you search and view repositories, manage issues and pull requests, read file contents, and interact with your GitHub account directly from your workspace.
The Google Drive integration lets you search, read, and manage files and folders in your Google Drive directly through Claude. Use it to access documents, create new files, organize content, and collaborate on shared resources without leaving your conversation.
The Gmail integration lets you read, search, send, and manage your email messages directly through AI conversations, enabling automated email workflows and intelligent inbox management.
The Brave integration lets you perform web searches using Brave Search directly from Claude, allowing you to retrieve up-to-date information, news, and web results without leaving your conversation.
Metorial helps you connect AI agents to Sentry with various tools and resources. Tools allow you to interact with perform specific actions, while resources provide read-only access to data and information.
Identify the authenticated user in Sentry. Use this tool when you need to: - Get the user's name and email address.
Find organizations that the user has access to in Sentry. Use this tool when you need to: - View all organizations in Sentry - Find an organization's slug to aid other tool requests
Find teams in an organization in Sentry. Use this tool when you need to: - View all teams in a Sentry organization - Find a team's slug to aid other tool requests
Find projects in Sentry. Use this tool when you need to: - View all projects in a Sentry organization - Find a project's slug to aid other tool requests
Find releases in Sentry. Use this tool when you need to: - Find recent releases in a Sentry organization - Find the most recent version released of a specific project - Determine when a release was deployed to an environment <examples> ### Find the most recent releases in the 'my-organization' organization ``` find_releases(organizationSlug='my-organization') ``` ### Find releases matching '2ce6a27' in the 'my-organization' organization ``` find_releases(organizationSlug='my-organization', query='2ce6a27') ``` </examples> <hints> - If the user passes a parameter in the form of name/otherName, its likely in the format of <organizationSlug>/<projectSlug>. </hints>
Get detailed information about a specific Sentry issue by ID. 🔍 USE THIS TOOL WHEN USERS: - Provide a specific issue ID (e.g., 'CLOUDFLARE-MCP-41', 'PROJECT-123') - Ask to 'explain [ISSUE-ID]', 'tell me about [ISSUE-ID]' - Want details/stacktrace/analysis for a known issue - Provide a Sentry issue URL ❌ DO NOT USE for: - General searching or listing issues (use search_issues) - Root cause analysis (use analyze_issue_with_seer) TRIGGER PATTERNS: - 'Explain ISSUE-123' → use get_issue_details - 'Tell me about PROJECT-456' → use get_issue_details - 'What happened in [issue URL]' → use get_issue_details <examples> ### Explain specific issue ``` get_issue_details(organizationSlug='my-organization', issueId='CLOUDFLARE-MCP-41') ``` ### Get details for event ID ``` get_issue_details(organizationSlug='my-organization', eventId='c49541c747cb4d8aa3efb70ca5aba243') ``` </examples> <hints> - If the user provides the `issueUrl`, you can ignore the other parameters. - If the user provides `issueId` or `eventId` (only one is needed), `organizationSlug` is required. </hints>
Get detailed information about a specific Sentry trace by ID. 🔍 USE THIS TOOL WHEN USERS: - Provide a specific trace ID (e.g., 'a4d1aae7216b47ff8117cf4e09ce9d0a') - Ask to 'show me trace [TRACE-ID]', 'explain trace [TRACE-ID]' - Want high-level overview and link to view trace details in Sentry - Need trace statistics and span breakdown ❌ DO NOT USE for: - General searching for traces (use search_events with trace queries) - Individual span details (this shows trace overview) TRIGGER PATTERNS: - 'Show me trace abc123' → use get_trace_details - 'Explain trace a4d1aae7216b47ff8117cf4e09ce9d0a' → use get_trace_details - 'What is trace [trace-id]' → use get_trace_details <examples> ### Get trace overview ``` get_trace_details(organizationSlug='my-organization', traceId='a4d1aae7216b47ff8117cf4e09ce9d0a') ``` </examples> <hints> - Trace IDs are 32-character hexadecimal strings </hints>
Download attachments from a Sentry event. Use this tool when you need to: - Download files attached to a specific event - Access screenshots, log files, or other attachments uploaded with an error report - Retrieve attachment metadata and download URLs <examples> ### Download a specific attachment by ID ``` get_event_attachment(organizationSlug='my-organization', projectSlug='my-project', eventId='c49541c747cb4d8aa3efb70ca5aba243', attachmentId='12345') ``` ### List all attachments for an event ``` get_event_attachment(organizationSlug='my-organization', projectSlug='my-project', eventId='c49541c747cb4d8aa3efb70ca5aba243') ``` </examples> <hints> - If `attachmentId` is provided, the specific attachment will be downloaded as an embedded resource - If `attachmentId` is omitted, all attachments for the event will be listed with download information - The `projectSlug` is required to identify which project the event belongs to </hints>
Search for events AND perform counts/aggregations - the ONLY tool for statistics and counts. Supports TWO query types: 1. AGGREGATIONS (counts, sums, averages): 'how many errors', 'count of issues', 'total tokens' 2. Individual events with timestamps: 'show me error logs from last hour' 🔢 USE THIS FOR ALL COUNTS/STATISTICS: - 'how many errors today' → returns count - 'count of database failures' → returns count - 'total number of issues' → returns count - 'average response time' → returns avg() - 'sum of tokens used' → returns sum() 📋 ALSO USE FOR INDIVIDUAL EVENTS: - 'error logs from last hour' → returns event list - 'database errors with timestamps' → returns event list - 'trace spans for slow API calls' → returns span list Dataset Selection (AI automatically chooses): - errors: Exception/crash events - logs: Log entries - spans: Performance data, AI/LLM calls, token usage ❌ DO NOT USE for grouped issue lists → use search_issues <examples> search_events(organizationSlug='my-org', naturalLanguageQuery='how many errors today') search_events(organizationSlug='my-org', naturalLanguageQuery='count of database failures this week') search_events(organizationSlug='my-org', naturalLanguageQuery='total tokens used by model') search_events(organizationSlug='my-org', naturalLanguageQuery='error logs from the last hour') </examples> <hints> - If the user passes a parameter in the form of name/otherName, it's likely in the format of <organizationSlug>/<projectSlug>. - Parse org/project notation directly without calling find_organizations or find_projects. </hints>
List all Sentry DSNs for a specific project. Use this tool when you need to: - Retrieve a SENTRY_DSN for a specific project <hints> - If the user passes a parameter in the form of name/otherName, its likely in the format of <organizationSlug>/<projectSlug>. - If only one parameter is provided, and it could be either `organizationSlug` or `projectSlug`, its probably `organizationSlug`, but if you're really uncertain you might want to call `find_organizations()` first. </hints>
Use Seer AI to analyze production errors and get detailed root cause analysis with specific code fixes. Use this tool when you need: - Detailed AI-powered root cause analysis - Specific code fixes and implementation guidance - Step-by-step troubleshooting for complex issues - Understanding why an error is happening in production What this tool provides: - Root cause analysis with code-level explanations - Specific file locations and line numbers where errors occur - Concrete code fixes you can apply - Step-by-step implementation guidance This tool automatically: 1. Checks if analysis already exists (instant results) 2. Starts new AI analysis if needed (~2-5 minutes) 3. Returns complete fix recommendations <examples> ### User: "What's causing this error? https://my-org.sentry.io/issues/PROJECT-1Z43" ``` analyze_issue_with_seer(issueUrl='https://my-org.sentry.io/issues/PROJECT-1Z43') ``` ### User: "Can you help me understand why this is failing in production?" ``` analyze_issue_with_seer(organizationSlug='my-organization', issueId='ERROR-456') ``` </examples> <hints> - Use this tool when you need deeper analysis beyond basic issue details - If the user provides an issueUrl, extract it and use that parameter alone - The analysis includes actual code snippets and fixes, not just error descriptions - Results are cached - subsequent calls return instantly </hints>
Search Sentry documentation for SDK setup, instrumentation, and configuration guidance. Use this tool when you need to: - Set up Sentry SDK in any language (Python, JavaScript, Go, Ruby, etc.) - Configure specific features like performance monitoring, error sampling, or release tracking - Implement custom instrumentation (spans, transactions, breadcrumbs) - Set up integrations with frameworks (Django, Flask, Express, Next.js, etc.) - Configure data scrubbing, filtering, or sampling rules - Troubleshoot SDK issues or find best practices This tool searches technical documentation, NOT general information about Sentry as a company. <examples> ### Setting up Sentry in a Python Django app ``` search_docs(query='Django setup configuration SENTRY_DSN', guide='python/django') ``` ### Setting up source maps for Next.js ``` search_docs(query='source maps webpack upload', guide='javascript/nextjs') ``` ### Configuring release tracking ``` search_docs(query='release tracking deployment integration CI/CD') ``` </examples> <hints> - Use guide parameter to filter results to specific technologies (e.g., 'javascript' or 'javascript/nextjs') - Include the programming language/framework in your query for SDK-specific results - Use technical terms like 'instrumentation', 'spans', 'transactions' for performance docs - Include specific feature names like 'beforeSend', 'tracesSampleRate', 'SENTRY_DSN' </hints>
Find guides and articles to help you get started with Sentry on Metorial.
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A comprehensive Model Context Protocol (MCP) server that provides deep integration with Sentry's error tracking and performance monitoring platform. This server enables AI assistants to search, analyze, and troubleshoot production issues, access detailed error information, query performance data, and navigate Sentry's extensive documentation—all through natural language interactions.
The Sentry MCP server bridges the gap between conversational AI and production monitoring by providing direct access to your Sentry data. Whether you need to investigate a critical error, analyze performance metrics, find documentation for SDK setup, or get AI-powered root cause analysis, this server offers a complete toolkit for working with Sentry through natural language queries.
Identify the currently authenticated user in Sentry. Returns the user's name and email address associated with the API token.
Parameters: None
List all Sentry organizations that the authenticated user has access to. Essential for discovering organization slugs needed for other operations.
Parameters: None
Discover teams within a specific Sentry organization. Useful for understanding team structure and finding team slugs for assignment or filtering purposes.
Parameters:
organizationSlug (required): The organization's slugregionUrl (optional): Region-specific URL for multi-region deploymentsList all projects within a Sentry organization. Projects are the primary organizational unit in Sentry where errors and performance data are collected.
Parameters:
organizationSlug (required): The organization's slugregionUrl (optional): Region-specific URL for multi-region deploymentsSearch for releases in a Sentry organization. Find recent deployments, locate specific version numbers, or determine when a release was deployed to an environment.
Parameters:
organizationSlug (required): The organization's slugquery (optional): Search string to filter releases by versionprojectSlug (optional): Limit results to a specific projectregionUrl (optional): Region-specific URL for multi-region deploymentsRetrieve the Data Source Name (DSN) configuration for a specific project. The DSN is required to configure Sentry SDKs in your applications.
Parameters:
organizationSlug (required): The organization's slugprojectSlug (required): The project's slugregionUrl (optional): Region-specific URL for multi-region deploymentsFetch comprehensive information about a specific Sentry issue including stack traces, metadata, tags, and occurrence patterns. Use this when you have a specific issue ID or URL and need detailed diagnostic information.
Parameters:
issueUrl (optional): Full URL to the issue in SentryorganizationSlug (optional): The organization's slugissueId (optional): Issue identifier (e.g., "PROJECT-123")eventId (optional): Specific event IDregionUrl (optional): Region-specific URL for multi-region deploymentsSearch for grouped issues using natural language queries. Returns a list of issues with metadata like title, status, user impact, and assignment. The AI automatically translates your natural language into Sentry's search syntax.
Parameters:
organizationSlug (required): The organization's slugnaturalLanguageQuery (required): Plain English description of what to search forprojectSlugOrId (optional): Limit search to a specific projectlimit (optional): Maximum results to return (1-100, default 10)includeExplanation (optional): Show how the query was translatedregionUrl (optional): Region-specific URL for multi-region deploymentsExamples:
Use Sentry's Seer AI to perform deep root cause analysis on production errors. Receives detailed explanations, specific code locations, concrete fixes, and step-by-step implementation guidance. The analysis is cached, so subsequent requests return instantly.
Parameters:
issueUrl (optional): Full URL to the issueorganizationSlug (optional): The organization's slugissueId (optional): Issue identifierinstruction (optional): Custom instruction for the AI analysisregionUrl (optional): Region-specific URL for multi-region deploymentsSearch for individual events and perform statistical aggregations. This is the primary tool for querying error logs, performance spans, and computing metrics like counts, averages, and sums. The AI automatically selects the appropriate dataset (errors, logs, or spans) and translates natural language into Sentry's query language.
Parameters:
organizationSlug (required): The organization's slugnaturalLanguageQuery (required): What you want to search for or calculateprojectSlug (optional): Limit to a specific projectlimit (optional): Maximum results (1-100, default 10)includeExplanation (optional): Show query translation detailsregionUrl (optional): Region-specific URL for multi-region deploymentsExamples:
Retrieve comprehensive information about a distributed trace including span breakdown, timing statistics, and service interactions. Provides a high-level overview with links to view detailed trace visualization in Sentry.
Parameters:
organizationSlug (required): The organization's slugtraceId (required): 32-character hexadecimal trace identifierregionUrl (optional): Region-specific URL for multi-region deploymentsDownload or list attachments associated with a Sentry event, such as screenshots, log files, or other files uploaded with error reports.
Parameters:
organizationSlug (required): The organization's slugprojectSlug (required): The project's slugeventId (required): The event identifierattachmentId (optional): Specific attachment to download; omit to list allregionUrl (optional): Region-specific URL for multi-region deploymentsSearch Sentry's comprehensive technical documentation for SDK setup guides, instrumentation instructions, configuration options, and integration tutorials. Covers all supported platforms and frameworks.
Parameters:
query (required): Search terms (2-200 characters)guide (optional): Filter to specific platform/framework (e.g., "javascript/nextjs", "python/django")maxResults (optional): Number of results (1-10, default 3)Examples:
Fetch the complete markdown content of a specific Sentry documentation page. Use paths obtained from search_docs results to retrieve full implementation details and code examples.
Parameters:
path (required): Documentation path (e.g., "/platforms/javascript/guides/nextjs.md")Access platform-specific SDK documentation for any supported Sentry platform.
URI Template: https://docs.sentry.io/platforms/{platform}/
Parameters:
platform: Platform identifier (e.g., "javascript", "python", "java")Access integration guides for specific frameworks within a platform.
URI Template: https://docs.sentry.io/platforms/{platform}/guides/{framework}/
Parameters:
platform: Platform identifierframework: Framework identifier (e.g., "nextjs", "django", "spring-boot")A pre-configured prompt that searches for all errors occurring in a specific file within your codebase. Useful for targeted debugging when you know which file is problematic.
Arguments:
organizationSlug (required): The organization's slugfilename (required): The filename to search forA guided prompt for getting AI-powered fixes for production issues. Automatically invokes Seer analysis and presents actionable remediation steps.
Arguments:
issueUrl (optional): Full URL to the issueorganizationSlug (optional): The organization's slugissueId (optional): Issue identifierIncident Response: Quickly investigate production errors by asking "show me critical issues from the last hour" and then diving into specific issues with "analyze this error and tell me how to fix it."
Performance Optimization: Query performance metrics with natural language like "what are the slowest database queries this week" or "show me API endpoints with response times over 2 seconds."
SDK Integration: Get instant access to setup documentation by asking "how do I set up Sentry in Next.js" or "show me Django configuration options."
Team Collaboration: Discover organizational structure, find project DSNs for team members, and track releases across environments.
Root Cause Analysis: Use Seer AI integration to get detailed explanations of complex errors, including specific code fixes and implementation guidance.
This MCP server communicates directly with Sentry's API using your authentication credentials. All queries respect your Sentry organization's access controls and permissions. No data is stored or transmitted to third parties beyond your Sentry instance.
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Metorial provides developers with instant access to 600+ MCP servers for building AI agents that can interact with real-world tools and services. Built on MCP, Metorial simplifies agent tool integration by offering pre-configured connections to popular platforms like Google Drive, Slack, GitHub, Notion, and hundreds of other APIs. Our platform supports all major AI agent frameworks—including LangChain, AutoGen, CrewAI, and LangGraph—enabling developers to add tool calling capabilities to their agents in just a few lines of code. By eliminating the need for custom integration code, Metorial helps AI developers move from prototype to production faster while maintaining security and reliability. Whether you're building autonomous research agents, customer service bots, or workflow automation tools, Metorial's MCP server library provides the integrations you need to connect your agents to the real world.