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"Understanding Prompts or Prompt Engineering" matching MCP servers:

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    A tutorial demonstrating how to build reusable, parameterized MCP prompt templates using FastMCP, including patterns for research, summarization, and code review.
    2
    MIT
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    quality
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    Analyzes, refines, and optimizes prompts for AI assistants by fixing grammar, improving clarity, applying best practices like chain-of-thought and few-shot learning, and scoring prompt quality across multiple dimensions.
    3
    16
    MIT
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    Enables natural language interaction with a GeoServer instance for managing workspaces, datastores, feature types, layers, styles, and OGC services (WMS/WFS) via an LLM-powered agent.
    1
    MIT
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    Enables AI agents to interact with Freeplay, an ops platform for AI engineering teams, to analyze production logs, identify quality issues, iterate on prompts and agents using real data, and run experiments before deploying.
    9
    2
    Apache 2.0
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    An MCP front-end for AnB. The tool surface is "use-don't-reveal": no tool returns a plaintext secret. Reveal paths require a TTY the server doesn't have, so the no-reveal guarantee is structural, not prompt-based — it holds even against a prompt-injected agent. Runs as a dedicated, narrowly-scoped AnB identity; exec is default-deny (only allowlist rules tagged scope=mcp run); command output
    5
    1
    MIT
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    AI infrastructure design agent. Describe your app in plain English; Riley designs, prices, and deploys AWS or GCP infrastructure with generated Terraform.
    24
    Apache 2.0
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    A bridge connecting AI agents to NCBI's PubMed database through the Model Context Protocol, enabling seamless searching, retrieval, and analysis of biomedical literature and data.
    11
    3,327
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    Apache 2.0
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    A Model Context Protocol server that provides AI assistants with plain-English access to official Dallas-area public data (weather alerts, school ratings, and 311 service requests) without requiring API keys or logins.
    4
    1
    Apache 2.0
  • F
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    A FastMCP server that exposes hospitality data — accommodations, events, and gastronomy — through a unified MCP interface, supporting multiple worlds for real or fictional data.
    5
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    Enables reading and writing YNAB budget data, such as listing budgets, accounts, categories, transactions, and creating or updating transactions, through natural language commands.
    8
    MIT