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"Godot Game Engine Development Resources" matching MCP servers:

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    An open-source MCP server that gives AI assistants comprehensive tools to read, write, run, and verify Godot projects, featuring a three-layer architecture (headless, editor, game bridge) with systematic security protections.
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    MIT
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    Enables AI assistants to control Unreal Engine via Remote Control API for game development automation, including asset management, actor control, level editing, animation, physics, visual effects, and cinematics creation through natural language.
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    MIT
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    A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.
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    MIT
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    Provides complete access to Model Context Protocol documentation through an MCP server, allowing LLMs to query specific sections like 'Tools', 'Resources', and 'Authorization' to retrieve comprehensive protocol specifications.
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    MIT
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    MCP server providing token-efficient access to OpenAPI/Swagger specs via MCP Resources for client-side exploration.
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    MIT
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    Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.
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    MIT
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    mistral-mcp is a TypeScript MCP server (spec 2025-11-25) that exposes the full Mistral AI API surface: 22 tools: chat, OCR, audio (Voxtral), vision, agents, embeddings, moderation, classification, files, batch, sampling, FIM (Codestral), streaming 2 resources: mistral://models, mistral://voices 6 curated prompts (French + English) with MCP argument completion Dual transport: stdio (default) + Str
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    MIT
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    A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.
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    MIT
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    Provides comprehensive documentation for MAX Platform, including Bot API endpoints, guides, Bridge API, and UI components, via MCP tools and resources for AI coding agents.
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    MIT
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    A production-grade TypeScript starter for building Model Context Protocol servers, supporting stdio and Streamable HTTP transports with modular tools, resources, and prompts.
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    A production-grade MCP server that provides real-time weather data and demonstrates the complete MCP protocol surface including tools, resources, prompts, and structured output.
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    DevEyes is a Model Context Protocol (MCP) server that captures screenshots from your local development environment and automatically optimizes them for LLM consumption.
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    MIT
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    A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.
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    Provides access to PatternFly React documentation, development rules, and component schemas through MCP tools, enabling AI assistants to help developers build applications with PatternFly components following best practices.
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    MIT
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    A CLI-based Model Context Protocol server that exposes PubNub SDK documentation and Functions resources to LLM-powered tools like Cursor IDE, enabling users to fetch documentation and interact with PubNub channels via natural language prompts.
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    Sleepycat