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"Enhancing Prompt Engineering with MCP" matching MCP servers:

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    An MCP server that gives an AI assistant a set of real mechanical-engineering tools. Provides deterministic tools like material properties, beam analysis, unit conversion, and curve fitting for engineering calculations.
    Last updated
    5
    MIT
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    Enables AI agents to generate, view, and analyze engineering diagrams (RF, PCB, EMC) in draw.io using natural language prompts, with auto-layout and 269 engineering stencils.
    Last updated
    10
    8
    AGPL 3.0
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    27 deterministic engineering compliance and calculation tools for the built environment (data-centre PUE and EED, EPBD, NIS2, Eurocode, UAE compliance), callable by AI agents via MCP and REST API. Free tier; every result cites the governing standard.
    Last updated
    MIT
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    Enforces team engineering standards across Git, code review, Rails, frontend, deployment, incidents, observability, API design, database, ADRs, and technical debt, with tools for branch name and commit message validation.
    Last updated
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    An MCP server that uses Claude 3.5 Sonnet to transform ordinary prompts into structured, professionally engineered instructions for any LLM. It enhances AI interactions by adding context, requirements, and structural clarity to raw user inputs.
    Last updated
    1
    3
    MIT
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    Optimizes prompts using meta-prompting techniques through a two-turn approach that first provides optimization guidelines and then refines the prompt for enhanced quality and effectiveness.
    Last updated
    1
    25
    4
    MIT
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    Enables dynamic prompt management by automatically discovering and serving markdown prompt files with YAML frontmatter via the Model Context Protocol.
    Last updated
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    1
    MIT
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    An MCP server that registers customizable prompt templates as tools for natural language interaction. It supports hot-reloading and easy extension via YAML or JSON files to automate tasks like code review, refactoring, and content summarization.
    Last updated
    2
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    1
    MIT
  • F
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    Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.
    Last updated
    2
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    A Model Context Protocol server that provides specialized prompt suggestions for backend development, frontend development, and general tasks to help LLMs generate better content.
    Last updated
    6
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    1
    MIT
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    A server based on Model Context Protocol that provides predefined prompt templates for tasks like code review and API documentation generation, enabling more efficient workflows in Cursor/Windsurf editors.
    Last updated
    10
    31
    246
    MIT