"Search Engine Optimization (SEO) Resources" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Read-only Amazon SES observability: search events, inspect bounces, pull delivery stats.
Health and token cost of every remote MCP registry server, probed daily. Look up, search, or probe.
Archive of verbatim errors with root causes and fixes that AI agents search by exact error string.
Ingest and search LogsLoom logs from coding agents.
Search + patterns, maturity assessment, context pricing, redaction checks - a practice as tools.
The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.
DevOps, SRE, and QA intelligence for Cursor — investigate bugs, assess release readiness, search logs, triage outages, diagnose failed CI, check deployments, and query connected cloud platforms. Secure remote MCP with OAuth2 and read-only QA subagents.
- ZopnightOAuthdev.zop.api
Read-only cloud cost and infrastructure governance across AWS, Azure and GCP. 85 tools covering cost overview and trends, cost by provider/resource/tag/team, budgets, resources, schedules, recommendations, tagging policies, audit logs, anomalies, Kubernetes resources and pod logs. Hosted remote server, nothing to install. Docs: https://zop.dev/learn/mcp-server?utm_source=glama&utm_medium=listing&utm_campaign=mcp-directory Claude setup: https://zop.dev/learn/how-to/set-up-zopnight-mcp-for-claude
heera.it via Agentimus: AI readiness, traffic, request log, search & index reports, by approval.
- gtmetrixOAuthcom.gtmetrix
Analyze web performance and get optimization insights from GTmetrix, directly in your AI workflow.
Search logs, investigate errors, check deployments, and monitor uptime for your elmah.io org.
MonoDuty MCP connects compatible assistants to uptime monitoring, job heartbeats and webhook alerts in an on-call workspace. Inspect monitoring coverage, prepare proposals, and create or manage supported resources with separate permissions. Hosted Streamable HTTP endpoint with OAuth. Requires an active verified MonoDuty account, workspace admin access and an API-eligible plan. Docs: https://monoduty.com/docs/mcp
High-performance array aggregation and metrics clearing engine. Cleans and bucket-groups noisy metric streams via an $O(N)$ single-pass data sweep. Operates natively with the pay-per-call x402 micropayment framework.
Search log events, investigate anomalies, and manage cases in your Knowledge Grid tenant.
The Polar Signals MCP server enables AI assistants to connect directly with performance profiling data, allowing users to analyze application performance through natural language queries. Key capabilities include querying CPU performance and memory usage, exploring profiling metadata like profile types and labels, and providing AI-driven code optimization suggestions directly within development environments like Claude Code or Cursor.
Production observability for AI agents: search runs, read evaluations, acknowledge incidents.
Live service status, active incidents, search, and outage history from Downtester.
Read-only access to Auralogs production logs: search logs, inspect errors, review AI analyses.
