"Understanding Inference Models" matching MCP servers:

Read-only MCP server for GenieLocker that exposes tools for service status, commercial inventory, live quotes, recipe search, and credit pricing, without enabling purchases or model inference.

Estimates GPU requirements, training/inference costs, and cloud-vs-on-prem TCO for AI workloads using deterministic calculators.

Official remote MCP server for RunComfy. 31 tools across three products: Serverless API (ComfyUI) deployment management and async inference, Model API hosted-model inference, and Trainer API LoRA training jobs.

Jungle Grid MCP Server lets AI agents submit, estimate, monitor, and retrieve logs for GPU workloads through Jungle Grid. It enables agentic execution for inference, training, fine-tuning, and batch jobs without manually choosing GPU providers or infrastructure.

Enables AI agents to discover models, pricing, and chat completions through RouterBase, an API gateway for 200+ AI models.

Compute price oracle for AI agents. Compare inference pricing across OpenAI, Anthropic, and DePIN providers like Hyperbolic. Get routing recommendations that save up to 80% on compute costs.

Enables AI models to interact with Akave's S3-compatible storage by providing tools for managing storage buckets and objects through standardized Model Context Protocol (MCP).

MCP server enabling AI models to list S3 buckets, objects, and download files securely.

Run, build, train, and deploy ML models on the cloud.

Enables AI assistants to provision and manage cloud infrastructure and AI/ML workloads—such as GPUs, nodes, storage, networking, databases, Kubernetes, and training/inference resources—through natural language. It also provides a universal REST tool for authenticated access to the underlying cloud API.

An implementation of the Model Context Protocol server that enables AI models to communicate with Edge Security Acceleration (ESA) services, allowing models to manage routines, deployments, routes, records, and sites through standardized protocols.

A read-only MCP server for the Cisco Meraki Dashboard API that exposes 50 GET endpoints for understanding network topology from organization down to individual devices and ports.

Connects Claude and other MCP-compatible AI assistants to a Coreflux MQTT broker, enabling them to discover and execute Coreflux commands for managing models, actions, rules, and routes through natural language.

Enables secure access to Xplainable AI platform capabilities for managing machine learning models, deployments, and preprocessors. Supports both read operations (listing models, deployments) and write operations (deploying models, generating reports) with proper authentication and rate limiting.

Enables managing Onde Inference accounts and model catalog operations through MCP tools such as login, app management, model registration, and assignment. Returns structured JSON over stdio for use with any MCP client.

Enables AI assistants to fetch live, dated prices for LLM models and cloud compute instances across providers, compare and recommend models, and estimate monthly costs based on workload-specific token shapes and constraints.

Enables large language models to directly access Tencent Cloud Log Service for log search, metric queries, and alarm management without code.

Enables LLMs to interact with Cloudera AI Workbench APIs for managing files, jobs, models, experiments, projects, and applications.

An MCP server that enables AI models to access user geolocation information through EdgeOne Pages Functions.

Enables AI models to interact with SQLite Cloud databases, supporting SQL queries, schema management, and performance analysis.