Unreal Engine Code Analyzer MCP Server

The Unreal Analyzer MCP Server bridges the gap between complex Unreal Engine codebases and AI assistants such as Claude or Cline. By exposing a rich set of analysis capabilities through the Model Context Protocol, it allows developers to query deep structural information about their C++ projects without leaving the AI workflow. This server solves a common pain point: understanding large, heavily‑templated Unreal code is time‑consuming and error‑prone when done manually. With the analyzer, an AI assistant can instantly retrieve class hierarchies, method signatures, and subsystem relationships, turning a tedious code‑review session into an interactive knowledge exploration.

At its core, the server offers several key features that empower developers:

• Class Analysis – Retrieve comprehensive details about any C++ class, including its methods, properties, and inheritance chain.
• Hierarchy Mapping – Visualize the entire class hierarchy for a subsystem, helping teams spot architectural patterns or potential refactors.
• Context‑Aware Code Search – Query the codebase with regular expressions or keyword patterns and receive results enriched with surrounding context.
• Reference Finding – Locate every occurrence of a class, function, or variable across the project, facilitating impact analysis when making changes.
• Subsystem Analysis – Drill down into major Unreal Engine subsystems (Rendering, Physics, etc.) to understand how they are implemented and interlinked.
• Pattern Detection & Learning – Identify common Unreal coding patterns and provide curated learning resources, making onboarding smoother for new team members.
• Custom Codebase Support – Extend the same analysis capabilities to any C++ project, from game engines like Unity or Godot to graphics libraries such as OpenGL and Vulkan.

These capabilities translate into real‑world use cases. A lead developer can ask the AI assistant to “show me all subclasses of that implement a custom physics update” and receive an instant, annotated list. A QA engineer might search for all instances of a deprecated API to prepare a migration plan, while a junior programmer can request the hierarchy of to understand rendering pipelines. Because the server communicates via MCP, any AI workflow—whether a chat interface or an integrated IDE plugin—can invoke these tools seamlessly.

Integration is straightforward: the MCP server registers a set of tools (e.g., , ) that the AI can call with natural language prompts. The assistant translates user intent into a tool invocation, receives structured JSON responses, and can even chain multiple calls (search → reference → hierarchy) to build complex queries. This tight coupling eliminates context switching, keeps developers focused on design decisions, and accelerates iteration cycles.

What sets the Unreal Analyzer apart is its combination of deep static analysis powered by Tree‑Sitter and a curated knowledge base of game‑genre patterns. Developers benefit from instant, accurate insights into Unreal’s intricate architecture and from AI‑guided learning resources that reduce onboarding time. Whether you’re maintaining a legacy engine build or prototyping a new rendering pipeline, this MCP server turns your AI assistant into a powerful code‑analysis partner.