Skip to main content
Glama
626,203 tools. Updated 2026-10-01 09:33

"A service for error tracking and performance monitoring" matching MCP tools:

  • Get real-time server metrics including uptime, error rate, and resource usage (CPU, memory, disk) for performance monitoring and capacity checks. Returns in-memory counters since server start.
    Academic Free v1.1
  • Retrieve logs and error messages for a specific Cloud Run service by providing the Google Cloud project ID, region, and service name.
    Apache 2.0
  • Stops a specified service in the Ambari cluster, returning request ID and status for progress tracking.
    MIT
  • Compare aggregate trace behavior between two time periods for a service to detect performance changes, such as slower operations or new error patterns.
    MIT
  • Fetch recent logs for a service over a look-back window with error/warning counts and top error patterns to investigate spikes. Filter with labels or aggregate server-side for counts.
    Apache 2.0
  • Detect latency and error-rate anomalies in a service by comparing recent behavior to a historical baseline, flagging statistically significant deviations that may indicate performance issues.
    MIT

Matching MCP Servers

  • A
    license
    B
    quality
    A
    maintenance
    Enables Claude/Lyra to create, monitor, and manage live sessions for long-running operations such as downloads, conversions, and agent jobs, with progress metrics, logs, error alerts, and a Textual dashboard; it also ingests updates from external media-server tools.
    12
    MIT

Matching MCP Connectors

  • Check service status, performance metrics, trust score, and pricing for crypto token risk intelligence. Verify the service is operational before making paid calls.
    MIT
  • Check service health via version, config presence, and API probe. Returns fixed status shape: healthy, degraded, or error, so monitoring never handles missing keys.
    MIT
  • Retrieve detailed information about a specific Railway service, including configuration, deployment status, and health metrics for monitoring and management.
    MIT
  • Retrieve detailed configuration, status, and health information for a specific Railway service to monitor deployments and check service details.
    MIT
  • Automates multi-step performance diagnosis by checking system counters, active services, error patterns, slow SQL, and service hotspots. Returns a severity-ranked diagnostic report with suggested actions.
    Apache 2.0
  • Get aggregated service-level performance stats to identify frequently called, error-heavy, or resource-intensive services, including external API summaries for dependency analysis.
    Apache 2.0
  • Starts a specified service in an Ambari cluster. Returns request details for progress tracking or an error on failure.
    MIT
  • Track error rate trends per service and minute to identify climbing error rates, services burning error budget, and prioritize rollback decisions.
    MIT
  • Retrieve comprehensive infrastructure monitoring and usage analytics, including security risk analysis and certificate expiry tracking, for compliance reporting and capacity planning.
    MIT
  • Monitor service dependencies by slug to track their status and receive alerts. Optionally specify a component and set alert sensitivity for targeted monitoring.
    MIT
  • Analyse sentiment and tone of global news coverage for a topic over time. Returns average tone scores, trend summary, and timeline for brand monitoring or tracking public sentiment.
    AGPL 3.0