Prompts

# prompts/my_prompts.py
from mcp.server.fastmcp import FastMCP
 
def register_my_prompts(mcp: FastMCP):
    """Register custom prompts."""
 
    @mcp.prompt()
    def analysis_prompt(
        topic: str = "",
        context: str = "",
        depth: str = "standard"
    ) -> str:
        """
        Structured analysis prompt for deep thinking.
 
        Guides the model through systematic analysis of any topic.
 
        Keywords: analysis, thinking, reasoning, deep-dive
        Category: reasoning
        """
        depth_instructions = {
            "quick": "Provide a brief 2-3 sentence analysis.",
            "standard": "Provide a thorough paragraph analysis.",
            "deep": "Provide comprehensive multi-paragraph analysis."
        }
 
        return f"""Analyze the following topic systematically.
 
## Topic
{topic}
 
## Context
{context if context else "No additional context provided."}
 
## Instructions
{depth_instructions.get(depth, depth_instructions["standard"])}
 
## Analysis Framework
1. **Key Concepts** - Identify main ideas
2. **Relationships** - How concepts connect
3. **Implications** - What this means
4. **Conclusions** - Summary and insights
"""
 
    print("Custom prompts registered")

from prompts.base_prompt import BasePrompt, simple_prompt
 
class ReasoningPrompts(BasePrompt):
    def __init__(self):
        super().__init__()
        self.default_category = "reasoning"
 
    def register_all_prompts(self, mcp):
        self.register_prompt(
            mcp,
            self.chain_of_thought,
            name="chain_of_thought",
            description="Step-by-step reasoning prompt",
            category="reasoning",
            tags=["thinking", "analysis", "step-by-step"]
        )
 
    def chain_of_thought(
        self,
        problem: str = "",
        constraints: str = ""
    ) -> str:
        return self.format_prompt_output(
            sections={
                "Problem": problem,
                "Constraints": constraints if constraints else "None specified",
                "Instructions": """Think through this step by step:
1. Understand the problem
2. Identify key factors
3. Consider approaches
4. Evaluate trade-offs
5. Provide solution"""
            }
        )
 
def register_reasoning_prompts(mcp):
    prompts = ReasoningPrompts()
    prompts.register_all_prompts(mcp)

# Format with sections
output = self.format_prompt_output(
    sections={
        "Context": "...",
        "Instructions": "...",
        "Output Format": "..."
    }
)
 
# Format with variables
output = self.format_prompt_output(
    content="Analyze {topic} for {user}",
    variables={"topic": "AI", "user": "John"}
)

system = self.create_system_prompt(
    role="You are an expert analyst.",
    capabilities=[
        "Deep analytical thinking",
        "Pattern recognition",
        "Clear explanation"
    ],
    constraints=[
        "Be concise",
        "Cite sources when possible",
        "Acknowledge uncertainty"
    ]
)

from prompts.base_prompt import simple_prompt
 
@simple_prompt(category="reasoning", tags=["analysis"])
def quick_analysis(message: str = "") -> str:
    """Quick analysis prompt."""
    return f"Briefly analyze: {message}"

result = await client.get_prompt("default_reason_prompt", {
    "user_message": "Explain quantum computing",
    "memory": "User prefers simple explanations",
    "tools": "search_web, calculate",
    "skills": "research_skill loaded"
})

result = await client.get_prompt("rag_reason_prompt", {
    "user_message": "Summarize these documents",
    "file_context": "...",
    "file_count": 3
})