"A server for improving AI math capability without using an API" matching MCP servers:

A read-only MCP server for querying AI provider administration APIs, providing normalized usage, cost, and dashboard data for OpenAI and Anthropic.

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.

Connects AI assistants to the Vectra AI security platform to enable intelligent analysis of threat detection data and automated incident response workflows. It allows users to investigate threats, take response actions, and generate security reports using natural language.

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.

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

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

MCP server for measuring, tracking, scoring, and improving AI agent reliability with tools for recording interactions, scoring reliability, analyzing failures, recommending improvements, generating audit reports, and checking MCP health.

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

Enables measuring, comparing, and health-checking endpoint response times through natural language, using tools to probe URL latency and compare two URLs.

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.

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.

Self-hosted AI orchestrator that monitors and manages homelab services, exposing them as MCP tools for LLMs to drive.

Transforms Elasticsearch into an AI-powered observability engine for analyzing logs, APM traces, and system metrics through natural language.

Enables LLMs to query real job data and summarize backend job failures using MCP tools backed by a SQLite database.

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

Enables AI assistants to query system health, metrics, service reconnaissance, run multi-node patrols, and send incident alerts across distributed infrastructure through MCP tools.

Enables benchmarking of Large Language Model APIs by measuring performance metrics such as generation throughput, prompt throughput, and Time To First Token (TTFT) with configurable concurrency levels and parameters.

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

Compresses log files into templates and statistics using Drain3, and exposes them to AI assistants via an MCP server for efficient log monitoring and anomaly detection.