"A guide for playing the game Satisfactory" matching MCP servers:

Bridges AI assistants to running game instances for testing, debugging, and verification. Works with any game engine via a simple TCP protocol.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

MCP server for running deterministic Godot game scenarios, listing available scenarios, running single or soak tests, and reading test reports.

Enables AI agents to create, run, and debug 2D games in a sandboxed engine, providing tools for simulation, state inspection, and quality validation.

Enables AI clients to validate game level progression data, audit localization packs for missing translations and dynamic-token mismatches, and run deterministic evaluations of generated puzzle or notification content.

An MCP server connecting Claude AI with game engine runtimes (Unity & Godot) for automated testing, log filtering, and scene hierarchy inspection.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Provides deterministic, offline, sourced resolutions for 44 mobile game development problems spanning performance, memory, rendering, store policies, IAP billing, crash vitals, live-ops emergencies, and store-policy deadlines, along with pre-launch checklists and launch-day runbooks. It also statically audits project directories for Google Play and App Store compliance, including target SDK, 16 KB ELF alignment, privacy manifests, and secret-file exposure, without any network calls or shell execution.

Exposes 11 agent-native QA tools over stdio so coding agents can discover a project, analyze risk, select the smallest relevant test set, generate and dry-run tests, triage failures, propose tiered heals, analyze flakes, generate quality reports, and evaluate release readiness. Planning and healing tools stay read-only or propose-only, while execution defaults to dry-run, keeping agent actions safe and evidence-backed.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

Zero-sidecar MCP server embedded directly in the Godot 4 editor as a GDScript EditorPlugin — no Node or Python sidecar. Reflection-driven tools over any engine class, validate-before-write GDScript, scene/script/resource authoring, and a runtime play-test loop (play, screenshot, input, assert).

Enables AI agents to create webhook URLs, wait for incoming deliveries, inspect payloads, and replay or send signed webhook events to a local handler.

Generates a pytest suite from acceptance criteria that are withheld from the coding agent, so the tests can disagree with the code. Four tools, and qikly_run never returns the criteria, which a test in the suite enforces.

MCP server that brings Trustabl static reliability scanning into Cursor, letting agents inventory agents/tools, flag risky patterns, score production readiness, and write SARIF reports.

A reference MCP server that enforces identity-aware tool access using role-based permissions (Reader, Analyst, Auditor) and supports multiple identity routes like Entra RBAC, Copilot Studio, and Okta XAA. It provides read-only access to test evidence with explicit denial paths for unauthorized tools.

Zero-dependency MCP server and CLI that proxies, inspects, and analyzes JSON-RPC message streams between MCP clients and servers.

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.

Enables checking npm packages for known security vulnerabilities using the OSV API before installation. Supports both single package checks and bulk vulnerability scanning for multiple packages at once.

A simple server implementing the Model Context Protocol (MCP) that echoes messages back, designed for testing MCP clients.

Bridges AI models with WinDbg to analyze Windows crash dumps and perform remote debugging through natural language queries, enabling execution of debugger commands and automated crash analysis.