Monitor Sentry Errors and Create Prioritized GitHub Issues

On-call engineers waste time manually triaging Sentry error alerts and creating corresponding GitHub issues. This workflow reads recent Sentry events, checks for existing GitHub issues covering the same error, and creates new prioritized issues with full stack trace context when none exist.

How the workflow runs

The scenario uses specific integration tools at each step, while Metorial keeps access scoped and visible.

  1. 1

    Search for existing issues covering the error

    Search GitHub issues for the Sentry error message or fingerprint to determine whether the problem is already tracked.

    • github:search
    • github:list_issues
  2. 2

    Ensure severity labels exist

    Check that labels for error severity levels exist in the repository and create any that are missing.

    • github:manage_labels
  3. 3

    Create a new issue for untracked errors

    Create a GitHub issue with the error title, affected environment, stack trace excerpt, occurrence count, and a link to the Sentry event.

    • github:manage_issue
  4. 4

    Comment on existing issues for recurring errors

    If a matching issue already exists, add a comment noting the new occurrence count or any change in frequency to keep context current.

    • github:comment_on_issue

Integrations used in this scenario

github

Search GitHub

Search the repository's existing issues for the Sentry error fingerprint or message to avoid duplicates.

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github

List Issues

List recent open issues to cross-reference with incoming Sentry errors.

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github

Manage Issue

Create a new GitHub issue with the error title, stack trace, frequency, and Sentry link.

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github

Manage Labels

Ensure the appropriate severity and error-type labels exist before applying them to the issue.

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github

Comment on Issue

Add a comment to an existing issue if a duplicate is found, noting increased frequency or a new occurrence.

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Connected systems

Integration

GitHub

Manage repositories, issues, and pull requests. Create and configure branches, star repositories, review code, and merge changes. Automate CI/CD workflows with GitHub Actions, manage workflow runs, secrets, and artifacts. Track issues with labels, milestones, and assignees. Search across code, repositories, issues, and users. Manage organizations, teams, and memberships. Create and manage projects, gists, packages, deployments, and environments. Access security alerts including code scanning, secret scanning, and Dependabot alerts. Read and write file contents in repositories. Manage webhooks, notifications, and codespaces.

View GitHub

Expected outcomes

Outcome 1

On-call engineers have structured GitHub issues ready for triage without manual error logging

Metorial keeps the workflow connected, governed, and traceable across the systems involved.

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Outcome 2

Duplicate issues are prevented, keeping the backlog clean and searchable

Metorial keeps the workflow connected, governed, and traceable across the systems involved.

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Outcome 3

Error context including stack traces and frequency is captured at issue creation time

Metorial keeps the workflow connected, governed, and traceable across the systems involved.

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How Metorial powers this scenario

Metorial is the governed connection layer between your AI agents and the tools your company runs on. It turns workflows like monitor sentry errors and create prioritized github issues into something you can deploy quickly, safely, and at scale.

Fast

Ready for your entire team

Connect 1000+ verified integrations through one Magic MCP URL instead of building and maintaining bespoke connectors for each system in this workflow.

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Secure

Guardrails on every action

Protoguard inspects every message and tool call for prompt injection and policy violations before an agent touches your systems.

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Enterprise

SSO, policies, and audit trails

Agents act on real identity under company SSO, with per-user and per-group access policies and a complete, searchable record of everything that happens.

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Team ready

Reusable across your org

Package this workflow as a skill, attach the tools it needs, and let teammates run it through Portals — governed by admins, owned by the people who do the work.

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Products behind this workflow

The Metorial products that connect, govern, and observe this scenario.

Connectivity

Integrations

Start from 1000+ verified integrations or bring your own, and give every one a governed path to your agents under existing SSO and access policies.

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Connectivity

Magic MCP

A single URL your AI client connects to. Sign in with the login you already use and your agent reaches every integration and tool you allow — no per-app setup.

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Identity

Access Control

Sign in with company SSO, set policies per user and group, and let agents act on real identity across every connected system in this workflow.

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Governance

Protoguard

Metorial’s security layer reviews every message and tool request before an agent acts — catching prompt injection and blocking anything outside your policies.

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Observability

Tracing

A complete, searchable record of everything your agents, team, and machines do across these integrations, so you can trust the workflow in production.

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Governance

Portals

Let teammates connect agents to the integrations and skills your company already uses, with admins deciding who gets access to what.

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Built for your whole team

However you adopt AI, Metorial has a path for connecting it safely.

Solution

For Agents

Give the agents behind this scenario governed access to every tool and integration they need, with one connection layer instead of bespoke glue code.

Agents solution

Solution

For Enterprise

SSO, granular access control, security review, and full audit trails so this workflow meets enterprise governance and compliance requirements.

Enterprise solution

Solution

For your Workforce

Let the people who do this work connect their own AI agents to approved integrations and reusable skills — safely, without waiting on engineering.

Workforce solution

Build this workflow with your own tools

Metorial gives teams one governed layer for connecting integrations to real production work.