"Automated Chat Service Based on Personalized Text Messaging Style" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Scan/purge hidden text & score web domains: TLS, DNS, headers, speed. Free scans, $0.01 actions.
Observed facts on public MCP servers: protocol checks, tool changes, signed evidence. No verdicts.
Public AI web-readiness scanner and machine-facing observability discovery service.
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.
Observatory operated and funded by devlo: real tools on frozen tasks; intervals, cost, limits.
AI/LLM agent output audit MCP: policy eval, tamper-evident chain, AI safety, x402 USDC on Base.
Manage cron/heartbeat checks, read pings and flips, pause/resume/delete on Healthchecks.io.
Read Spike.sh incidents, on-call, escalations and services; acknowledge, resolve, set priority.
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
Uptime, API and server monitoring with outages, reporting, on-call and status pages.
Read incidents, services, teams, on-call schedules; acknowledge, resolve and note incidents.
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.
Ecosystem monitoring: service status and x402 activity metrics
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.
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
Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith
EU AI Act Art-14 runtime oversight: allow / flag / gate-to-human on an agent action, with receipt.
Service level agreement monitoring for the Hive agent fleet
