Prompt Optimizer MCP Server

Instructions

Implementation Reference

• index.ts:74-106 (handler)

  Core handler function in PromptOptimizer class that executes the optimize_prompt tool logic: analyzes input prompt, applies optimization goals, computes improvements and score.

  async optimizePrompt(request: OptimizationRequest): Promise<OptimizationResult> {
    const { originalPrompt, context, targetAudience, optimizationGoals, style } = request;
  
    // 分析原始提示词
    const analysis = this.analyzePrompt(originalPrompt);
  
    // 应用优化策略
    let optimizedPrompt = originalPrompt;
    const improvements: string[] = [];
  
    // 应用选定的优化目标或默认目标
    const goals = optimizationGoals || ['clarity', 'specificity', 'structure'];
  
    for (const goal of goals) {
      const result = this.applyOptimization(optimizedPrompt, goal, context, targetAudience, style);
      optimizedPrompt = result.prompt;
      if (result.improvement) {
        improvements.push(result.improvement);
      }
    }
  
    // 计算改进评分
    const score = this.calculateScore(originalPrompt, optimizedPrompt, improvements);
  
    return {
      optimizedPrompt,
      improvements,
      reasoning: this.generateReasoning(originalPrompt, optimizedPrompt, improvements),
      originalLength: originalPrompt.length,
      optimizedLength: optimizedPrompt.length,
      score
    };
  }

• index.ts:327-360 (schema)

  Input schema and metadata definition for the optimize_prompt tool, including parameters like originalPrompt, context, goals, etc.

  const OPTIMIZE_PROMPT_TOOL = {
    name: "optimize_prompt",
    description: "优化和增强提示词以获得更好的 AI 交互效果。此工具分析提示词并应用各种优化策略来改善清晰度、具体性、结构和有效性。",
    inputSchema: {
      type: "object",
      properties: {
        originalPrompt: {
          type: "string",
          description: "要优化的原始提示词"
        },
        context: {
          type: "string",
          description: "优化过程中要考虑的额外上下文或背景信息"
        },
        targetAudience: {
          type: "string",
          description: "提示词的目标受众 (例如: '技术专家', '普通用户', '学生')"
        },
        optimizationGoals: {
          type: "array",
          items: {
            type: "string",
            enum: ["clarity", "specificity", "structure", "context", "actionable", "conciseness", "examples", "format"]
          },
          description: "要专注的具体优化目标。可用选项: clarity(清晰度), specificity(具体性), structure(结构), context(上下文), actionable(可执行性), conciseness(简洁性), examples(示例), format(格式)"
        },
        style: {
          type: "string",
          description: "优化后提示词的期望风格 (例如: 'formal(正式)', 'casual(随意)', 'technical(技术性)', 'creative(创意性)')"
        }
      },
      required: ["originalPrompt"]
    }
  };

• index.ts:385-387 (registration)

  Registers the optimize_prompt tool by including it in the response to ListToolsRequest.

  server.setRequestHandler(ListToolsRequestSchema, async () => ({
    tools: [OPTIMIZE_PROMPT_TOOL],
  }));

• index.ts:394-437 (handler)

  MCP CallToolRequest handler that dispatches calls to optimize_prompt, validates input, invokes PromptOptimizer, and formats response.

  server.setRequestHandler(CallToolRequestSchema, async (request) => {
    if (request.params.name === "optimize_prompt") {
      try {
        const args = request.params.arguments;
  
        if (!args || typeof args !== 'object' || !('originalPrompt' in args)) {
          throw new Error('缺少必需参数: originalPrompt');
        }
  
        const optimizationRequest: OptimizationRequest = {
          originalPrompt: args.originalPrompt as string,
          context: args.context as string | undefined,
          targetAudience: args.targetAudience as string | undefined,
          optimizationGoals: args.optimizationGoals as OptimizationGoal[] | undefined,
          style: args.style as string | undefined,
        };
  
        const result = await promptOptimizer.optimizePrompt(optimizationRequest);
  
        return {
          content: [{
            type: "text",
            text: JSON.stringify(result, null, 2)
          }]
        };
      } catch (error) {
        return {
          content: [{
            type: "text",
            text: `优化提示词时出错: ${error instanceof Error ? error.message : String(error)}`
          }],
          isError: true
        };
      }
    }
  
    return {
      content: [{
        type: "text",
        text: `未知工具: ${request.params.name}`
      }],
      isError: true
    };
  });

• index.ts:108-118 (helper)

  Helper method to analyze the original prompt's quality metrics like length, clarity, specificity, etc., used in optimization.

  private analyzePrompt(prompt: string): PromptAnalysis {
    return {
      length: prompt.length,
      hasContext: prompt.toLowerCase().includes('context') || prompt.toLowerCase().includes('background'),
      hasExamples: prompt.toLowerCase().includes('example') || prompt.toLowerCase().includes('for instance'),
      hasConstraints: prompt.toLowerCase().includes('must') || prompt.toLowerCase().includes('should') || prompt.toLowerCase().includes('requirement'),
      hasFormat: prompt.toLowerCase().includes('format') || prompt.toLowerCase().includes('structure'),
      clarity: this.assessClarity(prompt),
      specificity: this.assessSpecificity(prompt)
    };
  }