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GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
290+ quality-scored API capabilities for AI agents across 27 countries via 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/
Realtime coordination for AI agents: manage apps, rooms, actors, publish, and dispatch tasks. Visit https://nolag.app and setup your account.
Private work routing for authorized buyers and agents, with Zinvyl as the first enabled supplier.
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.
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.
Real-time status & uptime monitoring for 294 popular APIs — is it down, and how reliable?
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
Human-in-the-loop review and approval for AI agents. Audit trail, approval policies, native MCP.
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.
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.
