"Information about Unreal" matching MCP servers:

Provides build diagnostics and editor log tools for Unreal Engine AI development, enabling Live Coding builds, parsing compile errors, searching/filtering logs, and crash context.

An MCP server that complements Epic's official Unreal Engine MCP server with 78 additional tools across 14 subsystems for build/cook/package, cinematics, Niagara, automation testing, source control, profiling, World Partition, and project maintenance, using Unreal's built-in Python and Remote Control plugins.

Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.

An MCP server that turns Zod schemas into mocks, violations, and contract tests, enabling AI agents to reason about API contracts without manually crafting payloads.

Automated Playwright E2E test repair powered by a self-improving, governed MCP server that runs failing tests, collects failure artifacts, reasons about root causes, validates and applies fixes, and re-runs to verify.

Enables AI assistants to access RenderDoc capture data and assist with graphics debugging by retrieving draw calls, shader information, buffers, textures, and pipeline state.

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.

Enables playing and observing a running Unreal Engine 5 game through virtual gamepad, keyboard, and mouse input, plus screen capture, log streaming, and UMG UI inspection and control.

Allows LLM agents to query Playwright JSON test results for run summaries and failure information.

Local MCP server for querying VCD waveform files via SQLite; enables AI agents to ask precise questions about signal values, transitions, and clock cycles without dumping raw VCD text.

Enables defect management on the SEPP platform, allowing users to query defects, retrieve user project information, and set up automated monitoring with alerts for new or unresolved defects via webhook or email.

Enables AI assistants to analyze and inspect RenderDoc capture files, providing tools to examine draw calls, textures, buffers, and shader information. It allows developers to perform graphics debugging and resource analysis through natural language interactions.

Enables RTL simulation and hardware verification with Verilator through automatic testbench generation, natural language queries about simulations, waveform analysis, and protocol-aware testing for Verilog/SystemVerilog designs.

An MCP server that provides elicitation tools to interactively request user input, such as selecting options, providing information, or performing manual tests.

An MCP server for checking OWASP Top 10 vulnerabilities during API development testing. It analyzes API information and returns security assessment results to help developers identify potential security issues.

A server that converts Allure test reports into LLM-friendly formats, enabling AI models to better analyze test results and provide insights about test failures and potential fixes.

A testing server that demonstrates Model Context Protocol features, providing access to user data, todos, and system information through resources, tools for user management and calculations, and prompt templates for various analyses.

A frontend security dependency auditing tool that identifies vulnerabilities in local and remote repositories using the Model Context Protocol. It provides detailed audit information like CVSS scores and dependency chains, generating standardized markdown reports.

An MCP server that enables AI assistants to parse Xcode and Swift build outputs into structured, token-efficient formats like JSON or TOON. It provides tools for executing build commands and extracting detailed diagnostic information such as errors, warnings, and test failures.

Enables an agent to drive a running Unreal Engine game via UE4SS by reading/writing UObject properties and calling UFunction, with verdicts that verify whether the requested state change actually happened.