"Understanding the term 'flux' or its various applications" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Meter, cap, and block AI agent spend before the provider is charged.
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.
Fixter's MCP provides a stream-lined agentic way to onboard, setup and use the Fixter monitoring and observability platform. Check out more at https://fixter.dev/
Free-trial AI fleet spend meter. Quote agent fleet spend from token usage. 100 calls or 14 days. No auth. Official MCP Registry: io.github.mtardy90-sudo/bootlace-ai-spendmap.
Is GitHub, npm, Cloudflare or your AI provider down right now? 20 status pages, one call.
Oviond brings data from 100+ marketing platforms into one reporting platform. Through the Oviond MCP server, AI assistants can securely access and work with Oviond clients, projects, reports, dashboards, widgets, and marketing data. Ask questions about your reporting data, analyze marketing performance, and manage reporting workflows directly through your AI assistant.
Health and token cost of every remote MCP registry server, probed daily. Look up, search, or probe.
Wake me when my agent misses its heartbeat. Deadman, overrun, HTTP, TLS, content; US+EU nodes.
Verifies Bernstein run receipts and hash chains; lists the shipped presets and adapters. Read-only.
Private work routing for authorized buyers and agents, with Zinvyl as the first enabled supplier.
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.
Cookieless web analytics your coding agent reads: traffic answers, deploy impact, what broke. One connection covers every site on the account.
Read-only MCP for AI usage profiles, leaderboards, stats, and docs; no writes or private data.
Monitoring for the agent economy — liveness, latency, trust scoring for MCP endpoints
Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?
Human-in-the-loop review and approval for AI agents. Audit trail, approval policies, native MCP.
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.
The Cortex MCP server provides read-only access to real-time engineering context from the Cortex developer portal, allowing AI coding assistants to answer natural language questions about your organization's catalog (microservices, libraries, domains, teams, infrastructure), scorecards (engineering standards and best practices), initiatives (goals and deadlines), and Engineering Intelligence metrics. It includes tools for querying documentation, tracking personal entities, and accessing AI-assisted insights across the entire Cortex ecosystem.
