"Unity game development engine and related resources" matching MCP servers:

An MCP server providing 15 tools for Unity projects, including Unity Gaming Services LiveOps (Economy, Cloud Save, Cloud Code), build-size and bloat analysis, and store-compliance checks.

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

An MCP server that enables interaction with Google Cloud Game Services API, allowing users to manage game server deployments, realms, and configurations through natural language.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

MCP server for IBM Code Engine — build, push, and deploy containers from Cursor, Copilot, Claude, and Cline using natural language.

Enables satellite imagery analysis through Google Earth Engine, allowing users to search datasets, calculate vegetation indices like NDVI, filter collections by location and date, and export imagery to cloud storage. Supports major satellite datasets including Sentinel-2, Landsat, and MODIS for applications like agriculture monitoring and deforestation tracking.

Access your Databricks workspace through Claude and other LLMs. Query Unity Catalog tables, inspect jobs, and retrieve detailed metadata.

Enables AI agents to manage infrastructure by exposing Terraform tasks and deployments as tools via STDIO or SSE.

Deterministic AI data-center design tools for sizing, validation, and conceptual rack/site layouts. Supports NVIDIA Hopper, Blackwell, and Rubin profiles. Calculations require a registered AIDC API key; results preserve warnings, RFIs, and pending validations.

Enables conversational management of Hetzner Cloud, DNS, and Storage Box infrastructure through 137 MCP tools for CRUD operations and actions like server power control, DNS zone management, and storage box snapshots.

Generates tailored system architecture recommendations based on business parameters like QPS, concurrent users, database type, and AI model size, providing resource allocation plans, middleware suggestions, and exportable architecture diagrams.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

Connects to Oracle Autonomous Database via OCI Bastion tunneling to enable AI-powered database exploration. Supports schema introspection, automatic ERD generation, and read-only SQL query execution through natural language interfaces.

Stateless Streamable HTTP MCP endpoint with OAuth 2.1 authentication via Cloudflare Workers, supporting PKCE, DCR, and token introspection.

MCP server that enables AI agents to interact with Spica servers, managing databases, serverless functions, storage, authentication, auditing, debugging, and version control.

Enables AI agents to discover and invoke backend tools over MCP JSON-RPC while enforcing 3-legged OAuth 2.0 identity propagation, role-based access control, and protocol transcoding to REST APIs.

Enables AI assistants to authenticate against a cloud geospatial analysis platform, search and inspect its datasets, render them as maps, and compute statistics over specified regions. It exposes these capabilities as MCP tools that can be dropped into any Next.js project via a route-based adapter.

Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.

Enables users to query and visualize AWS spend and Amazon Bedrock usage data through natural language, including EC2 and service cost breakdowns and Bedrock usage by region, user, and model.