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Integrate Sentry MCP with your AI CRM

Investigate Sentry issues, events, projects, and application health.

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Explore Triggers and Actions

Analyze issue with seer

Use Seer to analyze production errors and get detailed root cause analysis with specific code fixes. Use this tool when: - The user explicitly asks for root cause analysis, Seer analysis, or help fixing/debugging an issue - You are unable to accurately determine the root cause from the issue details alone Do NOT call this tool as an automatic follow-up to get_sentry_resource. 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: "Run Seer on this issue" ``` analyze_issue_with_seer(issueUrl='https://my-org.sentry.io/issues/PROJECT-1Z43') ``` ### User: "Analyze this issue and suggest a fix" ``` analyze_issue_with_seer(organizationSlug='my-organization', issueId='ERROR-456') ``` </examples> <hints> - Only use when the user explicitly requests analysis or you cannot determine the root cause from issue details alone - Seer Autofix does not support metric alert issues (issueCategory: metric); use get_issue_details and search_events instead - 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>

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Execute sentry tool

Execute an available Sentry MCP tool discovered through search_sentry_tools. Use this tool when you need to: - Call a Sentry operation returned by search_sentry_tools - Execute a tool by name using arguments that match its returned schema <examples> execute_sentry_tool(name='find_projects', arguments={ organizationSlug: 'my-org' }) execute_sentry_tool(name='whoami', arguments={}) </examples> <hints> - Use search_sentry_tools first if you are not sure which name or arguments to pass. - Arguments are validated against the target tool's schema before execution. - Active organization, project, and region constraints are injected automatically. </hints>

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Find organizations

Find organizations that the user has access to in Sentry. Use this tool when you need to: - View organizations in Sentry - Find an organization's slug to aid other tool requests - Search for specific organizations by name or slug Returns up to 25 results. If you hit this limit, use the query parameter to narrow down results.

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Find projects

Find projects in Sentry. Use this tool when you need to: - View projects in a Sentry organization - Find a project's slug to aid other tool requests - Search for specific projects by name or slug Returns up to 25 results. When hasMore is true, use the query parameter to narrow down results.

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Get sentry resource

Fetch a Sentry resource by URL, or by resourceType plus resourceId. Pass a Sentry URL directly when possible; the resource type is auto-detected. Supports issues, events, traces, spans, AI conversations, replays, monitors, preprod snapshots, and snapshot images. Trace lookups return a condensed overview by default. AI Conversations: A conversation is a set of spans sharing the same gen_ai.conversation.id. Use resourceType='ai_conversation' with a conversation ID, or pass a Sentry conversation URL, to fetch the transcript/details. To discover or list conversations, use search_ai_conversations. Conversations are NOT issues — do not use search_issues for conversation queries. For preprod snapshot URLs (matching 'sentry.io/preprod/snapshots/'): - Without ?selectedSnapshot=: returns the snapshot diff summary (changed, added, removed images) - With ?selectedSnapshot=<image_file_name>: returns the image preview and metadata. Use the Sentry tool `get_snapshot_image` for full-resolution image bytes. Resource IDs: - monitor: <monitorSlug> - snapshot: <snapshotId> <examples> get_sentry_resource(url='https://sentry.io/issues/PROJECT-123/') get_sentry_resource(resourceType='issue', organizationSlug='my-org', resourceId='PROJECT-123') get_sentry_resource(resourceType='ai_conversation', organizationSlug='my-org', resourceId='conversation-123') get_sentry_resource(url='https://sentry.sentry.io/preprod/snapshots/123/') get_sentry_resource(url='https://sentry.sentry.io/preprod/snapshots/123/?selectedSnapshot=login_screen.png') </examples>

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Search events

Search Sentry events and replays. Use for event counts/statistics. `query` can be natural language or Sentry search syntax. With an agent configured, it fixes dataset, query, fields, and sort before running. Supports TWO query types: 1. AGGREGATIONS (counts, sums, averages): 'how many errors', 'total tokens' 2. Individual events with timestamps: 'error logs from last hour' Datasets: - errors: Exception/crash events with stack traces, usually grouped into issues - logs: Application log entries, including error-severity log messages - spans: Raw trace/span events for performance, AI/LLM calls, requests, and operations - metrics: Metric rows and aggregates: counters, gauges, distributions, values - profiles: Transaction/continuous profile results, profile IDs, profiled transactions - replays: Session replay results: rage clicks, dead clicks, visited pages, replay users If the user says logs, log messages, error logs, or warning logs, choose logs instead of errors. Replay searches return replay lists only; replay count()/avg()/sum() are not supported. NOT for grouped issue lists (use search_issues) or app screenshots/images (use get_latest_base_snapshot). <examples> search_events(organizationSlug='my-org', query='how many errors today') search_events(organizationSlug='my-org', dataset='errors', query='level:error') search_events(organizationSlug='my-org', dataset='errors', fields=['issue', 'count()'], sort='-count()') search_events(organizationSlug='my-org', dataset='spans', query='span.op:db', sort='-span.duration') search_events(organizationSlug='my-org', dataset='replays', query='count_errors:>0', sort='-count_errors') </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. - Use fields with aggregate functions like count(), avg(), sum() for statistics - Sort by -count() for most common, -timestamp for newest </hints>

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Search issues

Search for grouped issues/problems in Sentry - returns a LIST of issues, NOT counts or aggregations. Provide `query` as natural language or Sentry issue search syntax. When an embedded agent is configured, it fixes query and sort before running while preserving explicit Sentry search syntax. Returns grouped issues with metadata like title, status, and user count. Common Query Syntax: - is:unresolved / is:resolved / is:ignored / is:for_review / is:new / is:regressed / is:escalating - level:error / level:warning - firstSeen:-24h / lastSeen:-7d - assigned:me / assigned_or_suggested:me - release:latest - issue.category:feedback - issue.priority:high - environment:production - userCount:>100 DO NOT USE FOR COUNTS/AGGREGATIONS → use search_events DO NOT USE FOR individual events with timestamps → use search_events DO NOT USE FOR details about a specific issue → use get_sentry_resource <examples> search_issues(organizationSlug='my-org', query='critical bugs from last week') search_issues(organizationSlug='my-org', query='is:unresolved is:unassigned', sort='freq') search_issues(organizationSlug='my-org', query='level:error firstSeen:-24h', projectSlugOrId='my-project') </examples> <hints> - If the user passes a parameter in the form of name/otherName, it's likely in the format of <organizationSlug>/<projectSlugOrId>. - Parse org/project notation directly without calling find_organizations or find_projects. - The projectSlugOrId parameter accepts both project slugs (e.g., 'my-project') and numeric IDs (e.g., '123456'). </hints>

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Search sentry tools

Search the available Sentry MCP tool catalog by name and description. Many Sentry operations are intentionally not exposed as top-level tools. Use this for any Sentry-related task when you do not see an obvious direct tool, including long-tail inspection, project management, documentation lookup, preprod snapshots, attachments, DSNs, releases, teams, and issue-specific pivots. Use this tool when you need to: - Find the right Sentry operation for a task - Discover catalog tools and their schemas for a task - Inspect the executable JSON input schema for an available tool <examples> search_sentry_tools(query='list projects') search_sentry_tools(query='issue details') search_sentry_tools(query='find dsn', limit=5) search_sentry_tools(query='snapshot image') </examples> <hints> - Results only include tools available in the current session. - If a Sentry operation is not listed as a direct tool, search here before deciding it is unavailable. - Returned schemas already account for active organization, project, and region constraints. - Use the returned name and schema when executing a catalog result. - This tool returns structured JSON. Do not parse markdown from its text content. </hints>

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Update issue

Update a Sentry issue's status or assignment. Use this to resolve, reopen, assign, or ignore an issue. <examples> ``` update_issue(organizationSlug='my-org', issueId='PROJECT-123', status='resolved') update_issue(organizationSlug='my-org', issueId='PROJECT-123', assignedTo='user:123456') update_issue(organizationSlug='my-org', issueId='PROJECT-123', status='ignored') update_issue(organizationSlug='my-org', issueId='PROJECT-123', status='ignored', ignoreMode='forever') update_issue(organizationSlug='my-org', issueId='PROJECT-123', status='ignored', ignoreMode='untilOccurrenceCount', ignoreCount=100, ignoreWindowMinutes=60) update_issue(organizationSlug='my-org', issueId='PROJECT-123', status='ignored', reason='Ignoring because this is expected noise from the staging deploy') ``` </examples> <hints> - Provide `issueUrl` or `organizationSlug` + `issueId`. - At least one of `status` or `assignedTo` is required. - `assignedTo` format: `user:ID` or `team:ID_OR_SLUG`. - Use `execute_sentry_tool(name='whoami', arguments={})` to find your user ID for self-assignment. - Status values: `resolved`, `resolvedInNextRelease`, `unresolved`, `ignored`. - `status='ignored'` defaults to `ignoreMode='untilEscalating'`. - Ignore modes: `untilEscalating`, `forever`, `forDuration`, `untilOccurrenceCount`, `untilUserCount`. - Matching ignore inputs are `ignoreDurationMinutes`, `ignoreCount` + optional `ignoreWindowMinutes`, or `ignoreUserCount` + optional `ignoreUserWindowMinutes`. - To switch an already ignored issue between `untilEscalating`, `forever`, and condition-based ignore modes, first set `status='unresolved'`, then ignore it again with the new rule. - `reason` is optional. When provided, it will be posted as a comment on the issue's activity feed explaining why the action was taken. </hints>

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How the Sentry MCP integration works

The Sentry MCP integration connects your Dench AI CRM directly to Sentry MCP, so agents can read and act on your Sentry MCP data as part of everyday work — answering questions in chat, keeping your CRM in sync, and running automations without anyone copying data between tools.

9 actions are available for agents to invoke on your behalf. Every call runs through Sentry MCP's own authorization, scoped to the account you connect.

Set up Sentry MCP in Dench

  1. 1

    Sign in to your Dench workspace and open Integrations.

  2. 2

    Find Sentry MCP and click Connect — you'll authorize access through Sentry MCP's own sign-in flow. No API keys or code required.

  3. 3

    Ask an agent to use Sentry MCP in chat, or call it from an automation.

  4. 4

    Manage or disconnect the connection any time from workspace settings.

Frequently asked questions

How does the Sentry MCP integration work with Dench?

The Dench Sentry MCP integration connects your AI CRM to Sentry MCP, so AI agents can work with your Sentry MCP data as part of chats, automations, and CRM workflows. You connect your account once, and every agent in your workspace can use it — governed by your workspace permissions.

What actions can AI agents perform with Sentry MCP via Dench?

The Sentry MCP integration currently exposes 9 actions, including Analyze issue with seer, Execute sentry tool, Find organizations, Find projects, Get sentry resource, and Search events. Agents invoke them on your behalf from chat or from automations.

Do I need to write code to connect Sentry MCP to Dench?

No. You connect Sentry MCP from your Dench workspace using Sentry MCP's own sign-in and authorization flow — no API keys to copy, no glue code to maintain.

Is the Sentry MCP integration secure?

Connections are authorized through Sentry MCP's own authentication flow, and Dench stores only the authorization needed to act on your behalf. You can review and disconnect the Sentry MCP connection from your workspace settings at any time.

Sentry MCP | Dench AI CRM