mcp_prompt_mapper

Name: mcp_prompt_mapper
Author: Sumedh1599

@Sumedh1599

About 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

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

FAQ from mCP Prompt Mapper

What APIs does mCP Prompt Mapper support?

It supports Claude, Grok, and OpenAI APIs.

What output formats are available?

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

How do I install mCP Prompt Mapper?

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

What input format does `generate_prompts` expect?

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

Is mCP Prompt Mapper production‑ready?

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

Comments

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