"A guide to analyzing data effectively" 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/
Website traffic, human vs bot split, realtime visitors, breakdowns and site health for your DevDome sites. Hosted remote MCP server (streamable HTTP), authenticated with a DevDome API key.
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.
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.
Read-only MCP for AI usage profiles, leaderboards, stats, and docs; no writes or private data.
Watchdog for unattended AI agents: alerts, evidence checks and a verifiable proof per run.
Search + patterns, maturity assessment, context pricing, redaction checks - a practice as tools.
Public read-only demo of Netmon's network monitoring tools over a recorded snapshot.
Dead-man's-switch for cron jobs & AI agents. Import a crontab to arm one silent-miss alert per job.
Dead-man switch for cron and webhooks: ingest URL, miss detection, alerts and a status feed.
Report-To group count, body discarded
A managed runtime for custom API integrations. Manage lines, endpoints, keys, logs and DLQ via MCP.
Free MCP window into a live autonomous machine-economy experiment: telemetry, hypothesis scoreboard.
Read-only MCP access to sessions, funnels, campaigns, errors, live visitors, and anomalies.
MCP-native AI SRE: ask what's broken in production, get a reviewed GitHub fix PR.
Public MCP digital twin with synthetic systems and an agent firewall. No customer data.
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.
DriftOracle - 15 tools for model/data drift monitoring: PSI, KS-test, alerts, evidence packs.
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.
