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Fetch, discover, compose, and manage prompts from GitHub repositories via MCP.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Smart Prompts MCP Server" yet — see the docs or source repo.
Please intelligently discover available prompts from the specified GitHub repositories and list their names with brief descriptions by use case.
A list of discovered prompts from the repositories, each with a short usage description.
Select suitable prompts from this GitHub prompt collection and compose them into a more complete workflow prompt.
A complete composed prompt built from multiple prompts, with each part briefly explained.
Help me organize the prompts in this repository, group them by theme, and flag potentially duplicate or similar items.
An organized prompt structure grouped by theme, plus notes on duplicate or similar items.
Developers or product teams can use it to fetch and organize prompts from GitHub repositories in one place, reducing manual searching and copying. It is useful for centralizing scattered prompt assets.
When users do not know what prompts exist in a repository, they can use its intelligent discovery capability to quickly browse reusable content. This makes it easier to find prompts suited to the current task.
For more complex tasks, users can compose existing prompts into a more complete prompting flow. It is suitable for moving from isolated templates to a more structured workflow.
It is an enhanced MCP server for fetching prompts from GitHub repositories, with intelligent discovery, composition, and management capabilities.
According to the description, prompts come from GitHub repositories. For which repositories or content structures are supported, see the source repository.
The provided material does not include installation steps, runtime details, or key requirements. For exact setup details, see the source repository.
Manage, categorize, store, and quickly retrieve reusable AI prompts.
Manage and search prompt repositories directly from Claude Code or Codex.
Manage GitHub repositories, pull requests, issues, and workflows with natural language.
Rewrite rough prompts into optimized structured prompts for better LLM outputs.
Improve model outputs to expert-level quality through iterative creative direction.
Optimize prompts and agent scaffolding for cloud or local use.