"Using another LLM for research purposes" matching MCP servers:

Enables agents to check remaining Anthropic and OpenAI rate-limit quotas with reset times, plus Hermes Agent token usage, so bots can throttle or stop before hitting limits.

Measured latency and uptime for 45 hosted AI inference APIs: independent probes from 4 regions every 5 minutes, no gateway. Exposes get_ai_api_latency (TTFB p50/p95 and uptime rankings by region). Data CC BY 4.0.

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.

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.

LLM cost optimization and provider usage visibility for MCP-capable agents.

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.

MCP server for Tessera's LLM cost-optimization layer. Anchored spend, drift detection, recommendations as typed tools.

An MCP server that functions as an intelligent gateway for multiple LLM backends including OpenAI, Claude, and Ollama. It supports automatic provider fallback, streaming responses via Server-Sent Events, and real-time monitoring for robust AI integration.

A Model Context Protocol server for the AVEQ Surfmeter management API. It exposes typed tools for clients, measurements, anomalies, groups, ISPs, users, keys, capabilities, settings, license usage, and the built-in AI assistant.

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.

A specialized MCP server that helps analyze and debug Model Context Protocol logs by providing Claude with direct access to log files across multiple platforms.

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

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

Bridges AI models with WinDbg to analyze Windows crash dumps and perform remote debugging through natural language queries, enabling execution of debugger commands and automated crash analysis.

A standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports.

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.

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.

Exposes a CognOS agent system as a machine-readable JSON graph, enabling Claude to get a full system snapshot and inspect node status, edges, and blocked nodes.