"How to Assess the Security of a Python Application" matching MCP connectors:
Matching Connector Tools:
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/
CVE intelligence: exploitation (KEV/EPSS), detection coverage, fixed versions. All tools keyless.
Free anonymous website, DNS, email and TLS checks, plus read-only access to your monitors.
Free MCP window into a live autonomous machine-economy experiment: telemetry, hypothesis scoreboard.
Human-in-the-loop review and approval for AI agents. Audit trail, approval policies, native MCP.
Uptime watchdog and dead man switch for AI agents and cron jobs. Alerts you when a job goes silent.
EU AI Act Art-14 runtime oversight: allow / flag / gate-to-human on an agent action, with receipt.
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.
Measured latency & uptime for AI inference APIs, by region. Exposes a get_ai_api_latency tool.
Core Web Vitals metrics by CMS, CDN, and framework — free remote MCP, no auth.
Diagnose AI workflows for failure, security, and handoff risks — RED/AMBER/GREEN per node.
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.
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.
Connect engineering metrics, DORA performance, and deploy risk scoring to any AI assistant. Score PRs for deployment risk using a 36-signal model, query team health, incidents, coverage, and more.
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.