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MCP Prompt Mapper

@Sumedh1599

リポジトリ

基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

Sumedh1599

MCP Prompt Mapper について

Generates optimal Claude/OpenAI-ready prompts to build each part of the MCP server (resources, tools, prompts) from the input generated by `mcp_input_analyzer`.

#open-source#machine-learning#library#ai#prompt-templating

MCP Prompt Mapper の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp_prompt_mapper": {
      "command": "python",
      "args": [
        "setup.py",
        "install"
      ]
    }
  }
}

MCP Prompt Mapper のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is mCP Prompt Mapper?

mcp_prompt_mapper is an open‑source library that generates optimal prompts for Claude, Grok, and OpenAI APIs. It takes input from the companion mcp_input_analyzer and transforms it into structured, efficient prompts for building resources, tools, and additional prompts within an MCP server.

How to use mCP Prompt Mapper?

Install via pip (pip install mcp_prompt_mapper) or from source. In code, import PromptMapper, optionally specify output_format='json' or 'yaml', then call generate_prompts(input_data) with a dictionary. Examples for basic, YAML output, and streaming input are provided.

Key features of mCP Prompt Mapper

  • Prompt templating for resources and tools
  • Custom output formats: JSON and YAML
  • Cross‑API compatibility with Claude, Grok, OpenAI
  • Schema‑aware auto‑complete prompts
  • Streaming input parsing for Claude Desktop

Use cases of mCP Prompt Mapper

  • Generate optimised prompts from the mcp_input_analyzer for MCP server components
  • Create schema‑compliant resource and tool templates in JSON or YAML
  • Build prompts that work across multiple LLM APIs (Claude, Grok, OpenAI)
  • Process streaming input directly in Claude Desktop

よくある質問

1

What APIs does mCP Prompt Mapper support?

It supports Claude, Grok, and OpenAI APIs.

2

What output formats are available?

Prompts can be generated in JSON (default) or YAML format.

3

How do I install mCP Prompt Mapper?

Use `pip install mcp_prompt_mapper` or clone the repository and run `python setup.py install`.

4

What input format does `generate_prompts` expect?

It accepts a dictionary of input data, typically from `mcp_input_analyzer`.

5

Is mCP Prompt Mapper production‑ready?

The library is in early development; some tests may be failing. Contributions are welcome.

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