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351,855 tools. Last updated 2026-07-31 16:06

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

  • 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
  • Detect performance changes by comparing trace aggregates between two time windows for a service, showing per-operation latency and error rate differences.
    MIT
  • Detect latency and error-rate anomalies in a service by comparing recent traces against a historical baseline to identify performance issues.
    MIT
  • Stop monitoring a website's AI visibility and free up a monitoring slot. Use this to remove a site from scheduled tracking.
    Elastic 2.0

Matching MCP Servers

  • A
    license
    C
    quality
    D
    maintenance
    Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.
    Last updated
    40
    1
    Apache 2.0
  • A
    license
    -
    quality
    C
    maintenance
    Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.
    Last updated
    40
    MIT

Matching MCP Connectors

  • performance-review MCP — wraps StupidAPIs (requires X-API-Key)

  • Client-website monitoring for agencies: uptime, incidents, SSL/domain expiry, server metrics.

  • Retrieve detailed information about a specific Railway service, including configuration, deployment status, and health metrics for monitoring and management.
    MIT
  • Retrieve detailed information about a Railway service, including configuration, status, deployment details, and health monitoring.
    MIT
  • 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
  • Modify configuration for an existing Rybbit site. Toggle tracking features such as IP tracking, session replay, error tracking, and button clicks.
    MIT
  • Create, list, update, delete, and track Datadog Service Level Objectives (SLOs) with error budget and SLI status. Monitor reliability compliance and performance targets.
    Apache 2.0