"Connecting to an External API for Agent-Based Replies" matching MCP servers:

Dependency health checker for AI agent skills. Analyzes external endpoints for uptime, SSL validity, domain reputation, ownership changes, and abuse scores. Returns a 0-100 trust score per endpoint.

Measure the network path quality to a voice/VoIP destination and get an estimated MOS (ITU-T G.107 E-model) plus live RTT, jitter, and packet loss. Agent-native: REST + MCP, free tier then pay-per-call via x402.

Registers a set of inert, tempting decoy tools with any MCP-capable client so that any call from a hijacked or prompt-injected agent instantly raises an alert with full attack context and a per-call trace token. Also plants worthless canary tokens in honeypot files that trigger zero-false-positive leak alerts when they surface in agent output, files, or outbound requests.

MCP server for AI agent observability, providing trace and span logging, search, latency/tokens/cost metrics, and anomaly detection using an in-memory buffer.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

MCP server exposing AI agent observability tools: list, inspect, and deterministically replay recorded agent execution traces for debugging failures.

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9

Monitors API endpoint health by checking availability, measuring response times, and providing detailed status reports with error handling and timeout protection for the localhost:8080/api/ticket endpoint.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

Bridges with an installed API monitoring application to enable launching and status checks, live background capture, process attach, filter-tree inspection, GUI actions, and opening, validating, decoding, searching, inspecting, exporting, and comparing saved captures and related metadata.

Brings live project context into Slack via MCP, enabling developer teams to check service health, recall team decisions, search code, and query project context directly from chat.

Exposes rate-limit and usage data for AI coding agent CLIs as MCP tools, enabling querying of usage snapshots and reset times.

An MCP server that provides append-only, tamper-evident local receipts for AI agent actions, capturing command executions, outputs, and handoff evidence.

Shows your current Claude Desktop activity as Discord Rich Presence, including model, status, usage, and subscription info.

Enables natural language queries for AWS CloudWatch logs, metrics, and alarms via an LLM agent with MCP tools.

Scores AI agent trajectories and detects silent failures, loops, and reliability issues with zero external API cost.

MCP-based production monitoring agent for manufacturing OEE, providing real-time monitoring, downtime root-cause analysis, and automated alerts through integration with SQL Server, MES APIs, and incident management systems.

Local-first MCP server for credit risk analysis. It enables explainable rule discovery, statistical validation, PSI drift monitoring, and root-cause diagnosis on user-approved Parquet data while preserving privacy.

An MCP server that provides access to Google Cloud Monitoring API, enabling interaction with cloud resources monitoring data through natural language commands.