"Understanding Persistent Memory in Cursor Functionality" matching MCP connectors:

Real-time status for 75+ AI services (OpenAI, Anthropic, Cursor). No auth, CORS-enabled.

Live status and health checks for AI coding providers: Claude, Cursor, Copilot, Codex and more.

Uptime and website monitoring for AI agents. Query monitor status, incidents, heartbeats, domain expiry, and status pages in your Vantaj Uptime workspace.

Proxy Gemini (Vertex AI) completions wrapped in OpenTelemetry trace spans; returns the answer plus t

Track cost, latency, and usage of every MCP tool call from any client (Claude, Cursor, Windsurf). Free 25K calls/month — open-source proxy, EU-hosted.

Live status, API pricing and rate limits for ChatGPT, Claude, Gemini, Cursor and 42+ AI tools.

Analyze web performance and get optimization insights from GTmetrix, directly in your AI workflow.

Check infrastructure health, manage incidents, and run runbooks in Faultline.

Read-only Yandex Metrika MCP. Query visits, sources, geo, devices and more in plain language.

Register every AI agent, log every action, prove it. EU AI Act compliance built in.

MCP-native AI SRE: ask what's broken in production, get a reviewed GitHub fix PR.

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.

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

Hosted MCP server for Uptrack uptime monitoring. Manage monitors and incidents from AI agents like Claude, ChatGPT, and Cursor. OAuth 2.0 authentication.

Let AI agents monitor and manage your infrastructure through the Model Context Protocol. Query, create, and resolve — all in natural language.

The Polar Signals MCP server enables AI assistants to connect directly with performance profiling data, allowing users to analyze application performance through natural language queries. Key capabilities include querying CPU performance and memory usage, exploring profiling metadata like profile types and labels, and providing AI-driven code optimization suggestions directly within development environments like Claude Code or Cursor.