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    Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r
    1
    34 npm
    24
    MIT
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    Enables AI assistants to perform high-performance 3D CAD design, ultra-fast multi-view rendering, immutable versioned project management, and geometry/mesh verification for 3D printing on Windows.
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    Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.
    69
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    MIT
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    A meta-server that aggregates multiple MCP servers into a single interface, reducing token usage by 98%+ through progressive tool discovery and direct code execution that processes data between tools without consuming context window space.
    16 npm
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    Apache 2.0
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    Enables AI agents to generate dimensionally accurate mechanical parts (gears, enclosures, brackets, assemblies) in headless Blender from plain-English specs or JSON parameters, then verify them against manifold, bounding-box and print-production gates and export glTF/STL assets. It also scaffolds interactive Three.js CAD viewer pages with orbit controls, wireframe toggles and exploded-view scrubbing.
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    Enables AI agents to observe and control a browser-based 2D robot simulator, including driving, configuring sensors and modules, running programs, and generating wiring, firmware, and parts lists for ESP32, Arduino Uno, or Raspberry Pi.
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    MIT
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    Stop stitching context for Copilot and Cursor. With Sequa MCP, your AI tools know your entire codebase and docs out of the box.
    85 npm
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    MIT
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    MCP server for secure, session-based Python code execution in Docker containers, enabling LLM applications to run code, manage state, and access files.
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    MIT
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    Enables AI-native statistical analysis and reproducible research workflows through MCP, including natural language planning, protocol-based analysis, Python/R cross-validation, and publication-ready figure generation.
    MIT
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    Bridges a Roblox executor's DEX explorer with an AI client so the AI can see which instance the user has selected and, conversely, select, highlight, or inspect instances inside DEX on the user's behalf. It also exposes execution, inspection, remote-spy, and GUI tools to drive the live Roblox client over a local WebSocket bridge.
    96 npm
    MIT
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    An MCP server that exposes 252 algorithms from Knuth's TAOCP to AI agents, with safety guards and structured outputs for tasks like combinatorial generation, SAT solving, number theory, string analysis, graph algorithms, and symbolic math.
    MIT
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    MCP server for portable context management across AI assistants, providing tools to store and retrieve persistent context, instructions, and execute sandboxed bash commands with automatic git commits, using OAuth 2.1 and magic link authentication.
    1
    Apache 2.0
  • F
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    Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.
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    A lightweight Python-based server designed to run, manage and create CrewAI workflows using the Model Context Protocol for communicating with LLMs and tools like Claude Desktop or Cursor IDE.
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  • F
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    Enables AI-powered coding assistance including file editing, code generation, explanation, review, and shell command execution, using multiple free AI providers with automatic fallback.
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    Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.
    1
    MIT
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    Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26Γ— while keeping disabled upstream servers reachable.
    1
    674 npm
    MIT