"Finding the best servers for quant trading, options pricing in Python, R, Rust and market data" matching MCP servers:

Enables LLMs to query Azure service pricing via the public Azure Retail Prices API, with tools for searching prices, estimating costs, comparing regions, and listing services.

Provides Oracle Cloud Infrastructure pricing data to AI assistants, enabling cost estimation, shape comparison, and real-time pricing queries.

An MCP server that exposes AWS EC2 pricing data with an option to search by CPU, RAM, networking

An MCP server for accessing real-time AWS pricing information and providing cost analysis capabilities, with no AWS credentials required.

MCP server for generating upfront AWS service cost estimates and providing cost insights.

Azure VM sizes and USD list prices for 1,400+ sizes in 24 regions, refreshed weekly: find the cheapest size for vCPU, memory or GPU needs, estimate monthly cost with reservations and savings plans, and track weekly price changes.

A Model Context Protocol (MCP) server for producing better Terraform through CLI analysis (tflint, checkov, trivy, kics, infracost), best-practice guidance from terraform-best-practices.com, cloud provider recommendations (Azure, AWS, GCP), and Terraform Registry resource and module guidance.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

An open-source Model Context Protocol (MCP) server for the Open Telekom Cloud (OTC) Price Calculator API. Expose OTC pricing data to Claude and other LLM clients with full observability.

Enables access to cloud spot, on-demand, reserved, GPU rental, LLM token, and capacity pricing data with daily index fixings, using free tools and paid per-call payments over x402 or prepaid keys.

Enables users to describe an LLM fine-tuning job once and receive the cheapest, fastest, or most balanced GPU hardware options across a dozen cloud providers by calculating required VRAM/FLOPs and aggregating live pricing.

This MCP server enables querying Azure resource pricing programmatically through a structured workflow, including listing service families, service names, products, and calculating monthly costs.

Enables users to describe an LLM fine-tuning job and receive the cheapest, fastest, or most balanced GPU options across multiple cloud providers by calculating required VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job and receive ranked GPU recommendations across a dozen cloud providers based on estimated VRAM/FLOPs, live pricing, cost, and speed. It returns cheapest, fastest, and balanced hardware options without manual comparison.

Enables users to describe an LLM fine-tuning job once and receive VRAM/FLOPs-aware recommendations for the cheapest, fastest, or most balanced GPU options across a dozen cloud providers.

Enables querying Azure retail pricing information, comparing costs across regions and SKUs, estimating usage-based expenses, and discovering Azure services with savings plan information through the Azure Retail Prices API.

Enables users to describe a fine-tuning workload once and receive task-aware VRAM/FLOP estimates plus ranked cheapest, fastest, and balanced GPU options across multiple cloud providers. It can be used from Claude Code/Desktop or CLI/API to identify viable hardware options without manually comparing provider pricing.

Enables users to describe an LLM fine-tuning job in natural language and receive ranked GPU recommendations from a dozen cloud providers, based on estimated VRAM and FLOPs requirements. It surfaces the cheapest, fastest, and most balanced hardware options while disclosing the source and freshness of each price.

A Model Context Protocol server that enables programmatic querying of Azure resource pricing information from the Azure Retail Prices API through a structured four-step workflow.

Enables users to describe an LLM fine-tuning job once and get the cheapest, fastest, or most balanced GPU options across multiple cloud providers by estimating required VRAM and FLOPs.

Enables AI assistants to look up Oracle Cloud Infrastructure pricing and estimate monthly costs, including corrected PostgreSQL 4-SKU breakdowns, Windows licensing, and USD-to-BRL conversion with Brazilian tax gross-up. All estimates are paid-by-default, with Always Free applied only to network egress, public IPs, and VCN.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

MCP server that provides tools for automating AWS Pricing Calculator estimate generation.

Enables users to describe an LLM fine-tuning workload and receive ranked, cost- and runtime-optimized GPU recommendations across multiple cloud providers by estimating VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job and receive ranked, task-aware GPU recommendations with estimated VRAM/FLOPs, cost, and runtime across more than ten cloud providers.

Enables users to describe an LLM fine-tuning workload once and get task-aware VRAM/FLOPs estimates plus ranked cheapest, fastest, and balanced GPU recommendations across multiple cloud providers.

Enables users to describe an LLM fine-tuning workload once and get ranked, cost- and speed-optimized GPU recommendations across multiple cloud providers by estimating VRAM/FLOPs requirements.

Enables users to describe an LLM fine-tuning job once and get ranked GPU hardware recommendations with estimated VRAM/FLOPs, cost, and runtime across a dozen cloud providers.

It enables users to describe an LLM fine-tuning workload once and receive ranked GPU recommendations for cheapest, fastest, or balanced options across many cloud providers by estimating VRAM/FLOPs and aggregating live pricing.

It enables users to describe an LLM fine-tuning workload once and receive task-aware VRAM/FLOPs estimates plus ranked cheapest, fastest, or balanced GPU recommendations across multiple cloud providers.