techniques-for-improving-prompt-effectiveness MCP servers

"techniques-for-improving-prompt-effectiveness" matching MCP servers:

• Prompt for User Input MCP

  goldensansapple

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  Enables AI models to interactively prompt users for input or clarification directly through their code editor. It facilitates real-time communication between assistants and users during development tasks.

  Last updated 4 months ago

  MIT

• Prompt Ops MCP

  heyjustinai

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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 7 months ago

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  8

  4

  MIT

• Self-Improving Memory MCP

  SuperPiTT

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  Provides Claude with persistent memory and learning capabilities through 10 automatic agents that capture decisions, errors, solutions, and patterns across conversations. Features an anti-compaction system to prevent context loss and enables infinite conversation continuity.

  Last updated 4 months ago

  0

  MIT

• Refine Prompt

  FelippeFarias

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  security

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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 10 months ago

  1

  3

  MIT

• MCP Prompt Optimizer

  Bubobot-Team

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  This MCP server provides research-backed prompt optimization tools and professional domain templates designed to improve AI performance through strategies like Tree of Thoughts and Medprompt. It enables users to analyze, auto-optimize, and refine prompts using advanced reasoning patterns and safety-critical alignment techniques.

  Last updated 8 months ago

  20

  MIT

• Just Prompt

  disler

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  security

  F

  license

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  A lightweight MCP server that provides a unified interface to various LLM providers including OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama.

  Last updated 6 months ago

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