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Diagnose incidents with audited read-only access to ops tools and RCA.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-incident-copilot" yet — see the docs or source repo.
Using the current alert, related metrics, logs, recent deploys, and runbooks, investigate this production incident in timeline order and provide the likely root cause, impact scope, and recommended next steps.
An incident triage report with a timeline, key signals, likely root cause, impact assessment, and recommended actions.
Compare deploy records, alerts, logs, and metrics before and after the incident, determine whether the latest release caused it, and explain the supporting evidence.
A conclusion based on multiple operational signals explaining whether the deploy is linked to the incident and why.
Perform an end-to-end diagnosis of this incident and produce a verified root cause analysis summary, listing the alerts, metrics, logs, deploys, and runbook evidence used.
A structured RCA summary with conclusions and cited evidence sources.
After receiving an alert, an on-call engineer can use this tool to read alerts, metrics, logs, deploys, and runbooks to triage and localize the issue quickly. It fits environments that require auditability and do not want the tool to modify production systems.
When anomalies appear after a release, the team can cross-check deploy records with operational signals to determine whether the incident is change-related. It also helps assemble an end-to-end root cause analysis.
It is an MCP server that provides guarded, audited, read-only access to operational tooling, including alerts, metrics, logs, deploys, and runbooks. It also includes a triage agent that performs end-to-end incident diagnosis with CI-verified root cause analysis.
Based on the description, it provides read-only access. That means it is intended for querying, diagnosis, and analysis rather than making direct changes.
The provided material does not include installation steps or specify required keys, credentials, or runtime dependencies. See the source repository for exact prerequisites.
Safely triage incidents with evidence retrieval, ticket workflows, and notifications.
Enable AI assistants to query and manage ServiceNow incidents, users, and knowledge.
Diagnose system issues, monitor resources, inspect logs, and test connectivity.
Analyze MCP tool security risks, detect malicious behavior, and provide risk scores.
Monitor infrastructure drift and execute audited AI operations from one secure control plane.
Trace stack errors back to the commit and PR that introduced them.