"Guidance on connecting to Databricks" 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/
AI/LLM agent output audit MCP: policy eval, tamper-evident chain, AI safety, x402 USDC on Base.
Free anonymous website, DNS, email and TLS checks, plus read-only access to your monitors.
EU AI Act Art-14 runtime oversight: allow / flag / gate-to-human on an agent action, with receipt.
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.
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.
Read monitors, incidents, heartbeats, on-call and status pages; acknowledge or resolve incidents.
Read-only MCP access to sessions, funnels, campaigns, errors, live visitors, and anomalies.
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.
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.
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
Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith
Read Spike.sh incidents, on-call, escalations and services; acknowledge, resolve, set priority.
Manage cron/heartbeat checks, read pings and flips, pause/resume/delete on Healthchecks.io.
An MCP server giving access to Grafana dashboards, data and more.
Manage incidents and on-call: list/create/update incidents, who is on call, on-call overrides.