MCP Server Template

""" Text Processing Prompts Module Provides text-related prompts such as summarization requests. This module demonstrates migrating the existing prompt to the new structure. """ from fastmcp import FastMCP from .base import TextPrompt class TextProcessingPrompts(TextPrompt): """ Collection of text processing prompts. Provides summarization and other text processing prompts that were originally in the main.py file. """ def __init__(self): super().__init__(name="text_processing") # Set default template for summarization self.template = "Please summarize the following text:\n\n{text}" def register_with_mcp(self, mcp: FastMCP) -> None: """ Register text processing prompts with the FastMCP instance. Args: mcp: The FastMCP instance to register with """ # Register the summarize request prompt @mcp.prompt def summarize_request(text: str) -> str: """Generate a prompt asking for a summary.""" if not self.validate_text(text): return "Please provide valid text to summarize." self._log_prompt_call("summarize_request", text=text) return self.format_text(text) # Register additional text processing prompts @mcp.prompt def analyze_text(text: str, analysis_type: str = "general") -> str: """Generate a prompt asking for text analysis.""" if not self.validate_text(text): return "Please provide valid text to analyze." self._log_prompt_call("analyze_text", text=text, analysis_type=analysis_type) analysis_templates = { "general": "Please analyze the following text:\n\n{text}", "sentiment": "Please analyze the sentiment of the following text:\n\n{text}", "keywords": "Please extract keywords from the following text:\n\n{text}", "structure": "Please analyze the structure and organization of the following text:\n\n{text}" } template = analysis_templates.get(analysis_type, analysis_templates["general"]) return template.format(text=text) self.logger.info("Registered text processing prompts: summarize_request, analyze_text") def create_summary_prompt(self, text: str) -> str: """ Direct method for creating summary prompts (can be used internally). Args: text: Text to create summary prompt for Returns: Formatted summary prompt """ if not self.validate_text(text): raise ValueError("Invalid text provided") return self.format_text(text) def create_custom_prompt(self, text: str, instruction: str) -> str: """ Create a custom text processing prompt. Args: text: The text to process instruction: Custom instruction for processing Returns: Formatted custom prompt """ if not self.validate_text(text): raise ValueError("Invalid text provided") if not instruction.strip(): raise ValueError("Instruction cannot be empty") return f"{instruction}\n\n{text}"