"How to retrieve data from Power BI" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Read your team's hosted journal from an AI agent: every machine's streams, in hub order.
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.
Real-time status & uptime monitoring for 294 popular APIs — is it down, and how reliable?
Measured latency, time to first token and uptime for ~45 AI inference APIs, by region.
Monitor uptime and incidents, run checks, and publish status updates from your Uptimepage org.
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.
Ingest and search LogsLoom logs from coding agents.
Free spend report from an agent log, no key. Hosted proxies: caps, audit export, buy calls.
Read-only MCP for AI usage profiles, leaderboards, stats, and docs; no writes or private data.
Check if any website is down, from two continents, with uptime history and TLS expiry
Know when cron jobs and AI agents stop running: create monitors and check in from your agent.
Dead-man's-switch for cron jobs & AI agents. Import a crontab to arm one silent-miss alert per job.
Report-To group count, body discarded
Live status for 172 cloud and SaaS vendors from their official feeds. Is it you, or is it them?
Live reliability for AI agent tools: is it working right now, and how do I call it correctly?
Read-only MCP access to sessions, funnels, campaigns, errors, live visitors, and anomalies.
Public MCP digital twin with synthetic systems and an agent firewall. No customer data.
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.
