Monitoring and observability MCP servers for logs, metrics, traces and error tracking: let an AI assistant investigate incidents with real data. 699 servers in this category.
Verifies the liveness, schema integrity, and security of MCP and A2A endpoints to prevent tool poisoning and silent schema changes.
$claude mcp add --transport http arxiv-digest https://arxiv-digest.agentdiet.dev/mcpVerifies the liveness, schema integrity, and security of MCP and A2A endpoints to prevent tool poisoning and silent schema changes.
$claude mcp add --transport http alpha-stream https://alpha-stream.agentdiet.dev/mcp
Adds a status button to the DeepSeek Harness chat header to monitor connected MCP servers and their available tools.
An AI-powered network inventory system that reconciles a self-hosted asset list against live infrastructure like Docker, Proxmox, and UniFi.
Provides a read-only interface for AI clients to monitor Proxmox VE nodes, storage, guests, and task status without permission to mutate infrastructure.
Enables AI agents to monitor data quality, inspect lineage, and manage incidents across warehouses, lakehouses, and object stores.
Tracks and diffs daily changes in the AI industry including models, MCP servers, packages, reliability, and hiring trends.
Instruments APIs and AI agents to monitor tool calls, LLM traffic, and security events for threat detection.
Detects behavioral drift in LLM-driven autonomous systems using deterministic statistical methods and reference implementations.
Provides a machine-generated public record of Model Context Protocol server conduct and measurement verdicts.
Provides observability and governance for AI agents by auditing Claude sessions, tool calls, and costs through a SQLite-backed warehouse.
Lets AI clients call thousands of Alibaba Cloud OpenAPIs to manage, monitor, and audit cloud resources.
Provides a real-time telemetry dashboard and terminal visualizer to monitor tool mesh routing, token economies, and MCP server health.
Allows an AI agent to execute allowlisted PromQL queries on Mimir and retrieve Prometheus alerts.
Visualizes and diagnoses OpenClaw context window usage through terminal text, PNG images, and JSON data files.
Enables AI assistants to query and explore observability data including logs, metrics, and traces stored in OpenObserve.
Tracks and records text changes provided by MCP servers, skills, and plugins to an AI agent.
Tracks MCP protocol proposals, SDK changes, pull requests, releases, and security updates through evidence-linked monitoring.
Monitors autonomous agent telemetry using exponential decay liveness checks, latency drift detection, and Apdex performance metrics.
Monitors home lab infrastructure in real-time by tracking CPU, memory, disk, and network metrics through a dashboard.