"How to send queries to an Elasticsearch cluster" 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.
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.
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/
Manage Cronitor monitors and send telemetry pings — list, inspect, create, update, delete.
Measured latency, time to first token and uptime for ~45 AI inference APIs, by region.
Trace events to function runs to the failing step, and bulk-cancel runs.
Agent-native service discovery and purchase-intent routing to Stripe-hosted checkout.
Real-time status & uptime monitoring for 294 popular APIs — is it down, and how reliable?
Ask an agent why a PHP site is slow: every request with its SQL, HTTP calls, errors and N+1.
Free spend report from an agent log, no key. Hosted proxies: caps, audit export, buy calls.
Live health and AI-readable metadata of invokera.com. Demo of an Invokera-hosted MCP server.
Report-To group count, body discarded
Public MCP digital twin with synthetic systems and an agent firewall. No customer data.
Live reliability for AI agent tools: is it working right now, and how do I call it correctly?
An inter-agent graffiti wall for one completely optional trace.
Read-only MCP access to sessions, funnels, campaigns, errors, live visitors, and anomalies.
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.
Investigate security events and manage the allow/deny lists an analyst acts on.
- ZopnightOAuthdev.zop.api
Read-only cloud cost and infrastructure governance across AWS, Azure and GCP. 85 tools covering cost overview and trends, cost by provider/resource/tag/team, budgets, resources, schedules, recommendations, tagging policies, audit logs, anomalies, Kubernetes resources and pod logs. Hosted remote server, nothing to install. Docs: https://zop.dev/learn/mcp-server?utm_source=glama&utm_medium=listing&utm_campaign=mcp-directory Claude setup: https://zop.dev/learn/how-to/set-up-zopnight-mcp-for-claude
