"Overview of HTTP (HyperText Transfer Protocol)" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
Website traffic, human vs bot split, realtime visitors, breakdowns and site health for your DevDome sites. Hosted remote MCP server (streamable HTTP), authenticated with a DevDome API key.
Archive of verbatim errors with root causes and fixes that AI agents search by exact error string.
Test HTTP 429/503 retries and Retry-After with server-observed traces; share synthetic findings.
Free uptime monitoring: HTTP/TCP/TLS/DNS + MCP server checks, cron heartbeats, status pages, alerts.
Core Web Vitals metrics by CMS, CDN, and framework — free remote MCP, no auth.
Live health and AI-readable metadata of invokera.com. Demo of an Invokera-hosted MCP server.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Measured readings on open-source dependencies: health, end-of-life, model prices, incidents.
Track cost, latency, and usage of every MCP tool call from any client (Claude, Cursor, Windsurf). Free 25K calls/month — open-source proxy, EU-hosted.
Gain visibility into the performance, availability, and health of your apps and infrastructure.
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.
- 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
Mezmo MCP is a remote Model Context Protocol (MCP) server that lets AI assistants and IDE chat agents interact with the Mezmo observability platform via the Model Context Protocol. Use it for streamlined observability, log analysis, and root-cause analysis in your favorite tools. Add Mezmo MCP and you can: 🕵️ Run advanced Root-cause analysis over recent logs 📦 List and describe Pipelines 📤 Export and filter Logs with powerful query syntax
186 real AI agent post-mortems, 107 of them measurement failures. Free tools, paid via x402.
- Ionhour MCPOAuth unavailablecom.ionhour.api
Let AI agents monitor and manage your infrastructure through the Model Context Protocol. Query, create, and resolve — all in natural language.
The Buildkite MCP server exposes Buildkite product data (pipelines, builds, jobs, and test data) to AI tools, editors, and agents through the Model Context Protocol. It provides capabilities including pipeline creation and management, build monitoring with specialized tools like 'wait_for_build', efficient log querying using Apache Parquet conversion and caching, and OAuth-based authentication for both read-write and read-only access to Buildkite's REST API.
- BaromioOAuthio.baromio
Uptime, SSL, domain, and Core Web Vitals monitoring for websites and APIs. List, create, update, and pause monitors; read incident history with AI-generated diagnosis; pull Lighthouse and CrUX page speed data. OAuth 2.0 with dynamic client registration — works out of the box with Claude Desktop connectors. Free plan: 20 monitors, read-only MCP.
MCP-native AI SRE. Exposes your production OpenTelemetry problems, traces, and logs over the Model Context Protocol, plus an AI remediation loop that opens a reviewed GitHub fix PR and verifies in production (reopening on regression). Tools include list_problems, get_problem, query_traces, detect_anomalies, and request_problem_remediation. Human-in-the-loop by default — the merge button stays yours.
Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.
