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Vantage MCP Server

MCP Server

Speak natural language, get cloud cost insights

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Updated Aug 21, 2025

About

The Vantage MCP Server lets AI assistants and other MCP clients query your organization’s cloud spend data via natural language, bridging Vantage’s APIs to provide intuitive cost analysis.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Vantage MCP Server Demo

Vantage MCP Server – A Natural‑Language Bridge to Cloud Cost Insights

The Vantage MCP Server solves a common pain point for data engineers and finance teams: accessing complex cloud cost data through conversational AI. Instead of wrestling with API calls, VQL queries, or spreadsheet exports, developers can ask an AI assistant questions like “What was our AWS spend last month?” or “Show me the cost forecast for this quarter.” The server translates those natural‑language prompts into precise Vantage API requests, returning structured cost information that the AI can present in a friendly format.

At its core, the server is an open‑source Golang application that implements the Model Context Protocol. It exposes a rich set of tools—such as , , and —each mapping to a specific Vantage API endpoint. By providing these tools, the server enables developers to integrate cost analytics directly into their AI workflows without writing custom connectors. The tools support filtering by providers, services, tags, and budgets, giving users fine‑grained control over the data they retrieve.

Key capabilities include:

  • Unified cost querying via VQL, allowing complex filters and aggregations in a single tool.
  • Comprehensive metadata discovery with tools that list reports, integrations, budgets, dashboards, tags, and anomalies.
  • Accountability checks through , which reports workspace access levels for the authenticated token.
  • Feedback loops with , letting teams report issues or feature requests directly to the Vantage team.

Real‑world scenarios benefit from this architecture: a finance analyst can pull up monthly spend reports during a budgeting meeting, an engineer can quickly verify anomaly alerts in an incident response chat, and a product manager can compare forecasted versus actual costs while drafting a presentation—all via conversational AI. The server’s self‑hosted form supports local deployment with stdio transport, while a remote variant exists for cloud‑based setups.

By turning Vantage’s powerful cost analytics into an MCP‑compatible service, the Vantage MCP Server empowers developers to embed deep financial insights into AI assistants, streamlining decision‑making and accelerating cost‑management workflows.