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"MCP server that provides both prompts and resources" matching MCP servers:

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    A Model Context Protocol server for managing prompt templates as markdown files with YAML frontmatter, allowing users and LLMs to easily add, retrieve, and manage prompts.
    5
    25
    16
    MIT
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    LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.
    21
    1
    MIT
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    Provides AI assistants with access to a library of 924 free ecommerce marketing prompts across 43 categories, enabling tools to list collections, search prompts, and retrieve full templates with variables and recommended AI models.
    MIT
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    MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.
    MIT
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    Enables creation, management, and templating of prompts through a simplified SOLID architecture, allowing users to organize prompts by category and fill in templates at runtime.
    83
    117
    MIT
  • F
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    Enables AI assistants to register prompts for security verification, checking for hidden injections, data exfiltration patterns, and jailbreak attempts, then generate embed codes for displaying security badges on websites.
    4
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    Enables interaction with MongoDB databases through CRUD operations, aggregation, and schema discovery, with automatic field validation and ObjectId conversion.
    10
    11
    MIT
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    A Model Context Protocol server that generates prompts based on Git repository content, including a command to generate PR descriptions from diffs.
    3
    2
    MIT
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    A small, local, network-free MCP server for the RISEN prompt-engineering framework. It gives any MCP client tools to build, validate, save, and reuse structured prompts.
    8
    MIT
  • A
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    Lightweight MCP server for providing user prompts defined in Markdown with argument support.
    6
    BSD 3-Clause
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    Automatically extracts actionable methodologies from articles and URLs, stores them in a vector database, and retrieves relevant methods to enhance user prompts for more effective AI interactions.
    4
    MIT