Model Context Protocol (MCP)
Last updated 2026-06-04
The Model Context Protocol (MCP) is an open standard that lets AI assistants and coding agents connect to external tools and data sources in a uniform way, replacing one-off, custom integrations with a single shared interface. An MCP server exposes capabilities such as resources (readable data), tools (callable actions), and prompts, which any MCP-compatible client can discover and invoke at runtime. In FinOps, an MCP server lets an AI agent pull live cloud cost data and optimization recommendations directly into the development loop, so cost becomes part of how code is written and reviewed. For example, an agent can query the projected cost of a Terraform change or surface idle resources before a pull request merges, putting that information where engineers already work. LevelFour provides an MCP server, so engineers and their AI agents can check the cost of infrastructure before it is created, a practical form of Shift-Left FinOps.
Frequently asked questions
- What is the Model Context Protocol used for?
- MCP gives AI assistants and coding agents a uniform way to connect to external tools and data sources. Instead of building a custom integration for each system, developers run an MCP server that exposes resources, tools, and prompts any MCP-compatible client can discover and call at runtime.
- How does MCP help with cloud cost management?
- An MCP server can pull live cloud cost data and optimization recommendations into a developer's AI workflow. An agent can query the projected cost of an infrastructure change or flag idle resources during code review, making cost visible before resources are created rather than after the bill arrives.
LevelFour automates this across AWS, GCP, Azure, and Kubernetes with automated infrastructure-as-code pull requests.