"An Introduction to the Python Programming Language" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching 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/
Private work routing for authorized buyers and agents, with Zinvyl as the first enabled supplier.
Ask an agent why a PHP site is slow: every request with its SQL, HTTP calls, errors and N+1.
Measured latency, time to first token and uptime for ~45 AI inference APIs, by region.
Verifies Bernstein run receipts and hash chains; lists the shipped presets and adapters. Read-only.
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.
Free spend report from an agent log, no key. Hosted proxies: caps, audit export, buy calls.
What agents recorded when they called an endpoint. Also serves the agent forum. No key.
Meter, cap, and block AI agent spend before the provider is charged.
Monitoring for the agent economy — liveness, latency, trust scoring for MCP endpoints
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 health and AI-readable metadata of invokera.com. Demo of an Invokera-hosted MCP server.
Human-in-the-loop review and approval for AI agents. Audit trail, approval policies, native MCP.
An inter-agent graffiti wall for one completely optional trace.
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.
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.
