Oracle Cloud Infrastructure (OCI) MCP Server

The OCI MCP server bridges AI assistants and Oracle’s cloud platform by exposing a rich set of tools, resources, and prompts through the Model Context Protocol. It solves the common pain point of “cloud‑agnostic” assistants that lack native access to infrastructure data, enabling developers and operators to query, manage, and analyze OCI resources directly from an AI workflow. By standardizing the interface with MCP, the server allows Claude and other compliant assistants to discover compute instances, autonomous databases, object storage buckets, and more without embedding vendor‑specific SDK calls in the prompt logic.

What it does

The server offers a catalog of tools that perform discrete actions: listing compute instances, retrieving instance details, starting or stopping VMs, enumerating autonomous databases and storage buckets, and running quick security assessments. In addition to operational commands, it supplies resources such as compartment listings () that can be traversed by the assistant to build context. A dedicated prompt () equips the AI with domain‑specific language for analyzing OCI environments. All of these capabilities are accessed over a simple stdio transport, making integration with desktop assistants trivial.

Key features

• Comprehensive discovery – List and inspect compute, databases, storage, and network resources across compartments.
• Actionability – Start, stop, reset, or soft‑reset instances directly from a conversation.
• Security checks – Run conservative read‑only security heuristics to surface potential misconfigurations.
• Cost visibility – (Experimental) Summarize usage via the OCI Usage API, giving instant cost insights.
• Extensibility – The server is built on the official MCP Python SDK and OCI SDK, so adding new services (OKE, LB, Budgets) is straightforward.

Real‑world use cases

• Operational troubleshooting – An assistant can ask “What is the state of instance ?” and receive an immediate, up‑to‑date response.
• Incident response – During a security incident the AI can run and present findings without leaving the chat.
• Cost monitoring – Teams can query daily spend over a period and compare against budgets, all within the same conversation.
• CI/CD integration – Automation scripts can invoke to spin up test environments on demand, orchestrated by an AI‑guided workflow.

Integration with AI workflows

Because the server speaks MCP, any client that understands the protocol can issue calls and receive structured JSON responses. In practice, a developer adds the server to Claude Desktop’s configuration; from there, the assistant can call or as part of a prompt. The AI’s reasoning engine can then incorporate the returned data into explanations, recommendations, or next‑step suggestions. This tight coupling removes the need for custom API wrappers and keeps the conversational logic focused on high‑level intent rather than low‑level plumbing.

Standout advantages

• Vendor‑native access – Direct use of OCI’s official SDK ensures up‑to‑date features and consistent authentication via the standard .
• Security‑first design – All operations are read‑only or limited to explicit actions, reducing accidental exposure.
• Plug‑and‑play – The server’s simple stdio transport means it works out of the box with any MCP‑compliant client, from desktop assistants to serverless functions.

By exposing OCI resources through a unified protocol, the OCI MCP server empowers AI assistants to become true infrastructure collaborators, turning raw cloud data into actionable insights and automated actions within a single conversational interface.