"Understanding Inference Models" matching MCP servers:

Enables governance-grade AIops for GPU inference clusters with root-cause analysis, metrics, and policy-governed operations for vLLM and Ray.

Enables agents to inspect GPU status, size KV cache and vLLM/llama.cpp deployments, read live backend metrics, and run benchmarks over MCP.

Compare AI inference pricing across 9 providers in real time. Routing recommendations, spend tracking, and budget alerts for AI agents.

Enables classification of GPU workloads as training, inference, or idle from telemetry data, with tools for one-shot classification, benchmarking, and audit log verification.

An MCP server for the ProveTrade trade-audit stack that lets models validate CSVs, run paid audit runs, and check service health/deploy status via typed tools.

Read-only VMware vCenter/ESXi monitoring. 8 MCP tools for VM inventory, host status, datastore capacity, cluster info, alarms, events, and VM details. Code-level enforced safety — no destructive operations exist in the codebase. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.

Enables language models to read FortiGate/FortiOS firewalls and answer operational questions about firewall policies, network configuration, and live client state. Provides question-shaped diagnostic tools for reference checks, configuration searches, device lookups, routing, DHCP, ARP, wireless clients, and multi-appliance targeting without allowing configuration changes.

AI-powered VMware vCenter/ESXi monitoring and operations. 20 MCP tools for inventory queries, health monitoring, VM lifecycle management, fast provisioning (Linked Clone, OVA, template deploy), snapshot management, and datastore browsing. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.

Provides real-time visibility into Claude Pro and Max subscription usage limits directly within Claude Code by utilizing local OAuth tokens. It enables users to monitor session and weekly usage across different models and receive alerts regarding rate-limiting status.

This server acts as a MCP bridge to interact with the Cribl REST API. It allows AI models or other MCP clients to query and manage Cribl configurations.

Alephant MCP server for AI cost control, BYO-key routing, 50+ providers, and 320+ models.

A read-only MCP server that reports token usage by agents and models, and recommends the cheapest safe model and effort level for a given task, helping to reduce token waste.

Enables AI clients to query AxonHub admin data through natural language, including instance status, projects, channels, models, requests, and usage statistics, with read-only safeguards and sensitive-field redaction.

aimdb-mcp provides an MCP server implementation that enables Large Language Models to interact with running AimDB instances for introspection, debugging, and monitoring.

Real-time cluster health monitoring, pre-request NLMS latency prediction, and intelligent prompt routing across multi-instance LLM backends (vLLM, Ollama, SGLang, TGI).

Captures browser console messages (log, warn, error, etc.) and makes them available to AI language models like Claude Code and Gemini CLI for seamless debugging and development.

Provides access to real-time LLM pricing, speed metrics, and performance benchmarks for over 300 models from Artificial Analysis. It enables users to list, filter, and compare models based on costs, tokens per second, and intelligence indices.

Exposes a local inference ledger over MCP stdio, letting agents query request counts, token usage, TTFT, energy consumption, local costs, cloud-equivalent costs, savings percentages, and per-model breakdowns from an OpenAI-compatible proxy's SQLite ledger. Provides four read-only tools so coding agents can answer questions about home GPU inference economics without opening a browser.

Model Context Protocol (MCP) Server for Vunet vuSmartMaps - A multi-tenant observability platform integration. Query metrics, traces, logs, and data models from your Vunet tenants using natural language through AI assistants like Claude, GitHub Copilot, or any MCP-compatible client.

Enables language models to access LangSmith observability platform features including fetching conversation history, managing prompts, retrieving traces and runs, working with datasets and examples, and analyzing experiments.