The AppSignal MCP Node integrates securely with AppSignal's monitoring API through the Scalekit MCP gateway. It enables your AI agent to observe applications, inspect incidents, explore metrics, query logs and traces, manage dashboards, and configure triggers.
Parameters
Required Parameters
- action (string): The target AppSignal MCP tool action to run. Must be one of the enabled actions:
appsignalmcp_archive_trigger: Archive a trigger.appsignalmcp_create_dashboard_visual: Create a dashboard visual.appsignalmcp_delete_log_line_action: Delete a log line action.appsignalmcp_discover_metrics: Discover available metrics.appsignalmcp_get_anomaly_incidents: Retrieve anomaly incidents.appsignalmcp_get_app_resources: Retrieve application resources.appsignalmcp_get_applications: List applications.appsignalmcp_get_exception_incidents: Retrieve exception incidents.appsignalmcp_get_incident: Retrieve a specific incident.appsignalmcp_get_log_lines: Retrieve log lines.appsignalmcp_get_metric_names: Retrieve metric names.appsignalmcp_get_metric_tags: Retrieve metric tags.appsignalmcp_get_metrics_list: List metrics.appsignalmcp_get_metrics_timeseries: Retrieve metric timeseries data.appsignalmcp_get_more_tools: Discover additional tools.appsignalmcp_get_performance: Retrieve performance data.appsignalmcp_get_traces: Retrieve traces.appsignalmcp_get_triggers: List triggers.appsignalmcp_manage_dashboard: Manage dashboards.appsignalmcp_manage_incident_note: Manage incident notes.appsignalmcp_manage_log_line_action: Manage log line actions.appsignalmcp_manage_trigger: Manage triggers.appsignalmcp_reorder_log_line_actions: Reorder log line actions.appsignalmcp_update_dashboard_visual: Update a dashboard visual.appsignalmcp_update_incidents: Update incidents.
Optional Parameters
- params (object): A key-value dictionary containing action-specific inputs (e.g.,
{'app_id': 'my-app', 'incident_id': '12345'}).
Practical Use Cases
- Incident triage and diagnosis: Fetch exception and anomaly incidents, add notes, and update incident state automatically.
- Performance monitoring: Pull application performance metrics, traces, and timeseries to detect regressions and build reports.