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MCP Prompt Mapper

@Sumedh1599

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

Sumedh1599

关于 MCP Prompt Mapper

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 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

MCP Prompt Mapper 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

常见问题

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.

评论

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