"Unity" matching MCP servers:

A bridge between Unity and AI assistants that enables AI to interact with Unity game environments through a standardized interface for code execution, scene analysis, and runtime debugging.

A server that enables AI assistants to understand and interact with Unity projects in real-time, providing access to scene hierarchy, project settings, and the ability to execute code directly in the Unity Editor.

An MCP server that provides deterministic unit conversions backed by Pint, enabling exact unit conversions, compatibility checks, and parsing of quantities for LLMs.

Exposes Databricks REST APIs as MCP tools for managing and querying a Databricks workspace, including clusters, jobs, SQL, Unity Catalog, and more.

An MCP server that enforces unit testing standards by linting code and guiding agentic coding tools (like Gemini CLI or Claude Code) to follow best practices in test-driven development.

A deterministic unit conversion MCP server with fixed tables, offering tools to convert length, mass, temperature, and volume, list units, and compare quantities. Designed for judge-friendly schema clarity and no network I/O.

Enables AI assistants to analyze and manipulate Unity IL2CPP applications via Frida, supporting disassembly, class/method listing, and heap analysis.

Multi-protocol IPC adapter layer for integrating DCC software (Maya, Houdini, Blender, Unreal, Unity) with MCP, enabling tool registration and remote control across multiple transport protocols.

Unifies multiple MCP servers behind a single endpoint with lazy loading, auto-cleanup, Python plugins, and role-based filtering.

Enables AI assistants to interact with the Databricks platform through 263 tools and 8 prompt templates, covering Unity Catalog, SQL, Compute, Jobs, Pipelines, and more.

Enables reflective thinking and memory storage with support for multiple AI providers (OpenAI, Anthropic, Gemini, Ollama) or local fallback. Stores contextual memories locally and provides tools for reflection, questioning, note-taking, and summarization across different conversation keys.

Enables AI agents to access enterprise data from Unity Catalog (vector search, functions, Genie spaces) and perform developer actions in Databricks like managing notebooks and running jobs.

Normalizes heterogeneous trade data (FIX, JSON, CSV) into a unified schema and exposes query tools via MCP for natural language access.

A governed MCP server exposing Databricks operations as tools for jobs orchestration, SQL execution, notebook creation, Unity Catalog governance, lineage, clusters, and DLT pipelines, with safety features like dry-run and audit logging.