"Information about using cursors in Supabase" matching MCP servers:

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

A secure MCP proxy server with JWT authentication, SQL guardrails, rate limiting, and Kafka audit logging, enabling enterprise-grade access control for MCP clients like Cursor and Claude Desktop.

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A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.

Enables LLM clients to ask natural-language questions about nodes in a FABRIC slice, returning grounded answers from the Node Exporter Full dashboard's fixed PromQL queries.

Enables LLM clients to ask natural-language questions about FABRIC Testbed infrastructure metrics, with responses grounded in fixed Grafana/PromQL queries for node, switch, and link metrics.

Enables AI clients to create and configure monitors, subscribe to their evidence streams with durable cursors, and process observations with guaranteed at-least-once delivery.

Provides Claude with access to Shodan for IP address lookups, service discovery, and vulnerability scanning, allowing users to query information about hosts, count results, and check API usage.

Provides read-only access to query and retrieve information about devices, fleets, events, and configurations managed by Flight Control through a safe integration layer supporting filtering and selector-based queries.

Enables Alexa+ to answer plain-English questions about a home network using live diagnostics such as ping latency, bandwidth, connected devices, and interface health, with optional local or AWS Bedrock LLM reasoning and safe service restart tools.

Enables integration with Datadog APIs to monitor and retrieve information about monitors, metrics, dashboards, logs, events, and incidents through the Model Context Protocol.

Real-time conversation health monitor for AI agents that tracks structural dynamics like semantic drift and information gain using deterministic arithmetic, without calling an LLM.

Enables AI assistants to query and fetch error and performance monitoring data from AppSignal through the Model Context Protocol. Supports searching and retrieving detailed information about application errors and performance samples with flexible filtering options.

Enables comprehensive system monitoring and diagnostics through 18 tools that provide detailed information about CPU, memory, disk usage, network interfaces, running processes, battery status, hardware details, and temperature monitoring. Allows users to query system information and performance metrics through natural language interactions.

An AI agent system that monitors manufacturing equipment health using the Model Context Protocol (MCP). Enables answering natural language questions about equipment status, maintenance, and anomalies through MCP tools.

MCP-native agent evaluation and observability server. Log traces, evaluate output quality with 12 built-in rules (PII detection, prompt injection, cost thresholds), and track agent costs. Real-time dashboard, OTel-compatible spans. Self-hosted, MIT licensed.

Provides Claude with read-only access to PC diagnostics including hardware specs, live performance metrics, disk usage, network checks, and more, enabling natural language queries about PC health and performance.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.