"Information about ECharts - a data visualization library" matching MCP connectors:

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/

Uptime watchdog and dead man switch for AI agents and cron jobs. Alerts you when a job goes silent.

Measured latency & uptime for AI inference APIs, by region. Exposes a get_ai_api_latency tool.

Public MCP digital twin with synthetic systems and an agent firewall. No customer data.

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.

DriftOracle - 15 tools for model/data drift monitoring: PSI, KS-test, alerts, evidence packs.

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.

Mezmo MCP is a remote Model Context Protocol (MCP) server that lets AI assistants and IDE chat agents interact with the Mezmo observability platform via the Model Context Protocol. Use it for streamlined observability, log analysis, and root-cause analysis in your favorite tools. Add Mezmo MCP and you can: 🕵️ Run advanced Root-cause analysis over recent logs 📦 List and describe Pipelines 📤 Export and filter Logs with powerful query syntax

Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith

An MCP server giving access to Grafana dashboards, data and more.

Draw your app's architecture on a live canvas and flag the bottlenecks and security gaps.

API and website monitoring that validates the JSON a response returns, not just its status code. Create endpoint checks, pull incident reports carrying the actual failed payload, and read health scores from your editor.

Query real user session replay data: tapes, transcripts, error/rage-click filters, alerts.

Website performance monitoring: scans, Core Web Vitals, RUM data and alerts.

Interact with a global network measurement platform.Run network commands from any point in the world

High-performance array aggregation and metrics clearing engine. Cleans and bucket-groups noisy metric streams via an $O(N)$ single-pass data sweep. Operates natively with the pay-per-call x402 micropayment framework.

Connect AI assistants to AppAmbit — the command center for your mobile & desktop apps. Query real-time analytics, sessions, and crash reports; read and push remote config; send push notifications, provision and query managed per-app SQLite databases, deploy serverless Cloud Code functions; and manage a headless CMS. Also generates SDK setup snippets and runs integration diagnostics. Supports .NET MAUI, Swift, Objective-C, Android and more. Built for indie devs, mobile teams, and agencies.

Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.

Real User Monitoring for Core Web Vitals. Query LCP, INP, CLS field data from real visitors.