# CloudXray AI FinOps Directory [Health: Active]

**Category:** 💻 Developer Tools  
**Repository:** https://github.com/cloudxrayai/cloudxray-ai  
**GitHub Stars:** 0  
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**Directory Page:** https://allmcps.com/mcp/cloudxray-ai-finops-directory

## Description
Search and compare 290+ FinOps and cloud cost vendors from the CloudXray AI directory.

## Claude Desktop Quick Installation
Remote MCP endpoint (confidence: high). Install path detected from listing signals. Add as a URL/SSE server in your client:

```json
"mcpServers": {
  "cloudxray-ai-finops-directory": {
    "url": "https://cloudxray.ai/mcp"
  }
}
```

## Documentation

## What CloudXray AI FinOps Directory MCP server does

CloudXray AI FinOps Directory MCP server brings research from the CloudXray AI directory into supported AI assistants. The directory covers more than 290 FinOps and cloud cost management vendors. It is intended for teams comparing products for cloud cost visibility, allocation, chargeback, optimization, and related FinOps requirements.

The CloudXray AI FinOps Directory MCP server can search vendors using criteria such as capabilities, cloud platforms, integrations, and pricing models. It can also compare as many as four vendors, identify alternatives to a selected vendor, and show recent changes in the directory. These functions help turn a broad vendor search into a shortlist for further evaluation.

The repository also includes an optional FinOps vendor-selection skill. That skill provides a structured process for understanding the situation, relating needs to the FinOps Framework, building and comparing a shortlist, and preparing questions for vendor demonstrations. It cites CloudXray AI profiles as part of that process.

## How it works

The service is available at `https://cloudxray.ai/mcp` as a remote MCP server using Streamable HTTP. Clients can authenticate through OAuth sign-in or by sending an API key in an `Authorization: Bearer` header. The assistant calls the directory tools while handling a vendor research request, such as finding Kubernetes cost tools for EKS and GKE or comparing products for a multi-cloud environment.

The repository provides client-specific setup materials for Claude Code, Claude, Cursor, VS Code, and ChatGPT. It also documents a Gemini CLI path as planned. Other clients that support MCP can connect to the remote endpoint directly.

## Setup and configuration

A free CloudXray AI account with a verified email is required. Each account receives a free monthly allowance of calls. API and MCP usage is governed by CloudXray AI's API and MCP Terms.

For Claude Code, install the CloudXray plugin from the marketplace, then open the MCP configuration and authenticate the `cloudxray` server. Alternatively, add the remote HTTP endpoint manually with an API key. Claude users can add the endpoint as a custom connector; the optional skill is uploaded separately and requires Code execution and file creation to be enabled.

Cursor, VS Code, and ChatGPT have setup materials in their respective repository directories. A client without dedicated instructions can use the remote Streamable HTTP endpoint if it supports MCP authentication and connections.

## Tools and capabilities

The CloudXray AI FinOps Directory MCP server supports these documented tasks:

- Search vendors by capability, cloud, integration, pricing model, and other directory criteria.
- Compare up to four vendors.
- Find alternatives to a vendor.
- Review recent directory changes.
- Support a structured FinOps vendor-selection workflow through the optional skill.

The skill is distributed from the repository and packaged for supported platforms, including a skill archive for Claude and shared source used across platform-specific setup files.

## Limitations and notes

The service is research support rather than a substitute for vendor verification. Vendor information is produced through automated research reviewed by CloudXray AI, and important details should be confirmed with the vendors themselves.

Use also depends on account access and the monthly call allowance. The remote service is subject to the API and MCP Terms, while the repository itself is licensed under MIT. Gemini CLI is listed as planned in the repository rather than as a completed installation path.

_Full upstream README: https://allmcps.com/mcp/cloudxray-ai-finops-directory/readme_