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    Enables AI-driven creation of savable Wallpaper Engine web wallpaper source projects through a local STDIO service, with bounded project discovery, revision-checked file edits, checkpoint restore, validation, and publish staging. It also opens managed preview windows to set public properties and capture screenshots and bounded logs as runtime feedback from the official engine.
    12
    1
    MIT
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    Eyes for AI coding agents: deterministic MCP server that tells the LLM which CSS rule wins, in which file, on which line — and why. Cascade verdicts, blast radius, interaction timelines, pixel-perfect audits.
    22
    11 npm
    5
    Apache 2.0
  • F
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    MCP server (stdio, official Python SDK) exposing a single tool: quantity_execute. Performs dimensional calculation and unit conversion with evidence. Solves silent unit errors in LLM agent chains: 20 m/s × 3 h returns 216 km.
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    Enables programming agents to capture errors and conversation signals, reflect on root causes, consolidate reusable skills, and retrieve relevant context for future tasks, providing a self-learning memory loop.
    15
    MIT
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    Enables AI coding agents to spawn, parallelize, and synchronize multi-agent programming swarms through a stdio MCP interface. Provides tools for DAG-scheduled task dispatch, isolated Git worktree execution, atomic file locking, shared blackboard memory, and clean merging of completed agent work back to the main repository.
    1 npm
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    MIT
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    Enables MCP clients to run provider-backed reverse-engineering and software-analysis workflows for source code, binaries, and architecture, with evidence, limits, and optional external tool integrations.
    3 npm
    MIT
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    Provides CSS color utilities including parsing, conversion, gamut mapping, WCAG contrast, tint/shade ramp generation, and contrast-target solving.
    6
    75 npm
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    MIT
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    Enables AI agents to audit Core Web Vitals, transform HTML for speed, generate PWAs, and export performance configurations via the Model Context Protocol.
    8
    MIT
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    An MCP server that provides a multidimensional philosophical framework for prompt engineering by mapping intent across ten distinct branches of thought. It generates a principled construction basis, including active constructs and spectrum tensions, to guide the creation of structured and intentional prompts.
    4
    MIT
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    A Model Context Protocol (MCP) server that enables AI assistants to interact with Camunda Platform workflow engine. Provides 21 specialized tools for complete workflow automation and process management.
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    5
    MIT
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    A local-first, agent-agnostic MCP server that provides semantic search, persistent memory, and automated code review capabilities for development workflows. It leverages the Auggie SDK to offer advanced tools for codebase indexing, implementation planning, and deterministic static analysis.
    52
    48
    MIT
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    An MCP server that gives AI agents broad control over Unreal Engine 5.7, enabling actor/asset/level management, Blueprint and material creation, screenshots, automation, and arbitrary editor Python execution.
    35
    MIT
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    MCP server that launches Mesen/MesenCE headlessly and exposes the emulator's debugger-face Lua API over MCP JSON-RPC, enabling AI agents to load ROMs, step frames, inspect memory/registers, manage breakpoints/watches, trace execution, and export Code/Data Logger maps for SNES, NES, PC Engine, and Game Boy Advance.
    22
    GPL 3.0
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    Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.
    37 npm
    MIT
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    MCP server for managing and serving dynamic prompt templates using elegant and powerful text template engine. Create reusable, logic-driven prompts with variables, partials, and conditionals that can be served to any compatible MCP client like Claude Code, Claude Desktop, Gemini CLI, etc.
    18
    MIT
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    Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.
    MIT
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    Enables AI assistants to research the Asphalt 8 game engine through class-catalog lookup, Ghidra-based decompilation, notes, card writing, and quality checks, saving work to local drafts for later export and review.
    Apache 2.0
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    A local code-intelligence engine for AI agents that indexes repositories into a PostgreSQL-backed code graph and serves structured, token-budgeted context over MCP and HTTP, enabling targeted queries on symbols, dependencies, contracts, and impact analysis.
    7
    Apache 2.0