Vantage MCP Server

What does “Vantage” MCP Server do?

The Vantage MCP Server is an open-source tool written in Golang that connects AI assistants and MCP clients (such as Claude and Cursor) with your organization’s cloud cost data. Acting as a bridge to Vantage’s APIs, it enables users to query and analyze cloud spend data using natural language, making cost management and analysis more intuitive and accessible. By leveraging MCP (Model Context Protocol), the server empowers developers and stakeholders to ask questions about historical and current cloud expenditures, cost tagging, provider integrations, and more. Currently, the Vantage MCP Server is designed to be run locally, interfacing with clients via standard input/output (stdio) transport for seamless, secure, and straightforward integration into development workflows.

List of Prompts

(No explicit prompt templates are mentioned in the repository or documentation.)

List of Resources

(No explicit MCP “resource” primitives are documented in the repository or documentation.)

List of Tools

The Vantage MCP Server exposes the following tools, accessible from any compatible MCP client:

• query-costs
  General-purpose tool to fetch cost data using VQL.
• list-costs
  Displays all costs in an associated cost report.
• list-cost-reports
  Lists all cost reports available.
• get-cost-report-forecast
  Lists all forecasts of spending related to a cost report.
• list-cost-integrations
  Lists all cost provider integrations (e.g., AWS, Azure, GCP) and their associated accounts.
• list-cost-providers
  Lists the providers that the workspace has shared.
• list-cost-services
  Lists all services and their associated provider shared with the workspace.
• list-budgets
  Lists all budgets available to compare against a cost report.
• list-dashboards
  Lists all dashboards created in the Vantage account.
• list-tags
  Lists tags that can be used to filter cost reports.
• list-tag-values
  Lists tag values that can be used to filter cost reports.
• list-anomalies
  Lists anomalies detected on cost reports.
• list-unit-costs
  Retrieves the unit costs for a given cost report.
• get-myself
  Utility to list available workspaces and check the access level of your auth token.
• submit-user-feedback
  Sends feedback about the MCP or Vantage experience to the Vantage team.

Use Cases of this MCP Server

• Cloud Cost Analysis
  Developers and finance teams can interactively query historical and current cloud spend data, making cost analysis accessible through natural language.
• Provider Integration Review
  Easily list and examine cloud provider integrations (AWS, Azure, GCP) and their accounts to ensure correct and up-to-date connections.
• Budget Tracking
  Retrieve and monitor budgets, compare them with actual spending, and get forecasts to manage resources efficiently.
• Anomaly Detection
  Identify unexpected cost spikes or anomalies in real-time to quickly address potential issues or overspending.
• Cost Tag Management
  Retrieve, list, and manage tags and tag values used for filtering and organizing cost reports, enabling granular cost allocation.

How to set it up

Windsurf

1. Prerequisites:
   Ensure you have Go and Node.js installed.
2. Locate configuration:
   Open the Windsurf configuration file.
3. Add Vantage MCP Server:
   Insert the following JSON under the mcpServers section:

   {
     "vantage-mcp": {
       "command": "vantage-mcp-server",
       "args": [],
       "transport": "stdio"
     }
   }
   

4. Save and restart:
   Save the file and restart Windsurf.
5. Verify setup:
   Confirm the server is running and accessible from Windsurf.

Claude

1. Prerequisites:
   Ensure Go and Node.js are installed.
2. Locate configuration:
   Edit your Claude desktop configuration (e.g., claude_desktop_config.json).
3. Add Vantage MCP Server:
   Example:

   {
     "mcpServers": {
       "vantage-mcp": {
         "command": "vantage-mcp-server",
         "args": [],
         "transport": "stdio"
       }
     }
   }
   

4. Save and restart:
   Save the configuration and restart Claude.
5. Verify setup:
   Interact with the MCP Server via Claude.

Cursor

1. Prerequisites:
   Install Go and Node.js.
2. Locate configuration:
   Open the Cursor settings file.
3. Add Vantage MCP Server:

   {
     "mcpServers": {
       "vantage-mcp": {
         "command": "vantage-mcp-server",
         "args": [],
         "transport": "stdio"
       }
     }
   }
   

4. Save and restart:
   Restart Cursor to initialize the MCP server.
5. Verify setup:
   Test querying costs or dashboards.

Cline

1. Prerequisites:
   Ensure Go and Node.js are installed.
2. Locate configuration:
   Edit the Cline configuration file.
3. Add Vantage MCP Server:

   {
     "mcpServers": {
       "vantage-mcp": {
         "command": "vantage-mcp-server",
         "args": [],
         "transport": "stdio"
       }
     }
   }
   

4. Save and restart:
   Save changes and restart Cline.
5. Verify setup:
   Check for successful connection to the MCP server.

Securing API keys using environment variables

Store sensitive API credentials in environment variables instead of config files. Example configuration:

{
  "mcpServers": {
    "vantage-mcp": {
      "command": "vantage-mcp-server",
      "args": [],
      "env": {
        "VANTAGE_API_KEY": "your-api-key"
      },
      "transport": "stdio"
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "vantage-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent can use this MCP as a tool with access to all its functions and capabilities. Remember to change “vantage-mcp” to your actual MCP server name and replace the URL with your own MCP server URL.

Overview

Our opinion

The Vantage MCP Server offers a robust set of cloud cost analysis tools and integrates well with major MCP clients. However, it lacks explicit documentation of prompt templates, resource primitives, roots, and sampling support. Overall, it’s highly practical for its domain but could improve on protocol feature completeness.

MCP Score