"API documentation for creating mock data for frontend development" matching MCP servers:

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

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.

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

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

MCP server that integrates with VictoriaMetrics vmanomaly API to enable AI-assisted anomaly detection, model management, and configuration generation.

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.

An MCP server that gives AI assistants the ability to connect to, query, profile, and monitor data sources — turning any LLM into an interactive data engineering copilot.

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.

Enables access to SORACOM IoT platform data including Harvest sensor data, file storage, SoraCam camera footage/events, and SIM statistics through authenticated API calls.

MCP server that unifies real-time telemetry from industrial systems into a single queryable interface, enabling production visibility, anomaly detection, and operational insights.

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 endpoint availability monitoring and HTTP health checks for single or multiple URLs.

Enables AI clients to investigate data engineering workflows by exposing tools for job status, logs, schema lookup, read-only SQL, and searching documentation/incidents, along with resources and prompts for ETL failure analysis.

An MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.

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.

Enables searching for relevant tables and retrieving data from Microsoft Sentinel's data lake using natural language, supporting security hunting scenarios like password-spray detection and impossible travel checks.

Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.

Enables Claude Code to query fleet telemetry data for device health summaries, anomaly detection, capacity breach forecasts, and incident history via narrow MCP tools.

Connect AI assistants to live Meta Ads, GA4, and Google Search Console data. 100% local, credentials machine-locked and encrypted. Supports Claude Desktop, Cursor, Windsurf, Cline, and more.