Chain of Draft (CoD) MCP Server

Instructions

Implementation Reference

• index.js:662-681 (handler)

  Handler for the 'logic_solve' tool in the MCP callTool request handler. Invokes the core Chain of Draft reasoning client with domain set to 'logic' and formats the response.

  if (name === "logic_solve") {
    const result = await chainOfDraftClient.solveWithReasoning({
      ...args,
      domain: "logic"
    });
    
    const formattedResponse = 
      `Chain of ${result.approach} reasoning (${result.word_limit} word limit):\n\n` +
      `${result.reasoning_steps}\n\n` +
      `Final answer: ${result.final_answer}\n\n` +
      `Stats: ${result.token_count} tokens, ${result.execution_time_ms.toFixed(0)}ms, ` +
      `complexity score: ${result.complexity}`;
    
    return {
      content: [{
        type: "text",
        text: formattedResponse
      }]
    };
  }

• index.js:505-526 (schema)

  Input schema definition for the logic_solve tool, used in tool listing.

  const LOGIC_TOOL = {
    name: "logic_solve",
    description: "Solve a logic problem using Chain of Draft reasoning",
    inputSchema: {
      type: "object",
      properties: {
        problem: {
          type: "string",
          description: "The logic problem to solve"
        },
        approach: {
          type: "string",
          description: "Force 'CoD' or 'CoT' approach"
        },
        max_words_per_step: {
          type: "number",
          description: "Maximum words per reasoning step"
        }
      },
      required: ["problem"]
    }
  };

• server.py:122-140 (handler)

  Handler function for logic_solve tool in FastMCP server. Registered via @app.tool() decorator (which infers schema from parameters). Delegates to chain_of_draft_solve with domain='logic'.

  @app.tool()
  async def logic_solve(
      problem: str,
      approach: str = None,
      max_words_per_step: int = None
  ) -> str:
      """Solve a logic problem using Chain of Draft reasoning.
      
      Args:
          problem: The logic problem to solve
          approach: Force "CoD" or "CoT" approach (default: auto-select)
          max_words_per_step: Maximum words per step (default: adaptive)
      """
      return await chain_of_draft_solve(
          problem=problem,
          domain="logic",
          approach=approach,
          max_words_per_step=max_words_per_step
      )

• index.js:309-420 (helper)

  Core ChainOfDraftClient.solveWithReasoning helper implementing the reasoning logic (complexity estimation, approach selection CoD/CoT, prompt creation, Anthropic Claude API call, response extraction, format enforcement, analytics logging). Used by all domain tools including logic_solve.

  async solveWithReasoning(params) {
    const {
      problem,
      domain = 'general',
      max_words_per_step = null,
      approach = null,
      enforce_format = true,
      adaptive_word_limit = true
    } = params;
    
    const startTime = Date.now();
    
    // Analyze problem complexity
    const analysis = complexityEstimator.analyzeProblem(problem, domain);
    const complexity = analysis.estimated_complexity;
    
    // Determine word limit
    let wordLimit = max_words_per_step;
    if (!wordLimit && adaptive_word_limit) {
      wordLimit = complexity;
    } else if (!wordLimit) {
      // Default based on domain
      wordLimit = complexityEstimator.domainBaseLimits[domain] || 5;
    }
    
    // Determine approach (CoD or CoT)
    const performanceStats = analyticsDb.getPerformanceByDomain(domain);
    const selectedApproach = approach || 
      reasoningSelector.selectApproach(domain, complexity, performanceStats);
    
    // Create prompt based on approach
    const prompt = selectedApproach === 'CoD' 
      ? createCodPrompt(problem, domain, [], wordLimit)
      : createCotPrompt(problem, domain, []);
    
    // Call Claude
    const response = await anthropic.messages.create({
      model: 'claude-3-sonnet-20240229',
      max_tokens: 1000,
      messages: [
        { role: 'user', content: prompt }
      ]
    });
    
    // Extract reasoning and answer
    const fullText = response.content[0].text;
    
    // Extract final answer (assuming it comes after the reasoning, often starts with "Answer:" or similar)
    let reasoningSteps = fullText;
    let finalAnswer = '';
    
    // Common patterns for final answer sections
    const answerPatterns = [
      /(?:Final Answer|Answer|Therefore):?\s*(.*?)$/is,
      /(?:In conclusion|To conclude|Thus|Hence|So),\s*(.*?)$/is,
      /(?:The answer is|The result is|The solution is)\s*(.*?)$/is
    ];
    
    // Try to extract the final answer with each pattern
    for (const pattern of answerPatterns) {
      const match = fullText.match(pattern);
      if (match && match[1]) {
        finalAnswer = match[1].trim();
        reasoningSteps = fullText.substring(0, fullText.indexOf(match[0])).trim();
        break;
      }
    }
    
    // If no pattern matched, just use the last sentence
    if (!finalAnswer) {
      const sentences = fullText.split(/[.!?]+\s+/);
      if (sentences.length > 1) {
        finalAnswer = sentences.pop().trim();
        reasoningSteps = sentences.join('. ') + '.';
      }
    }
    
    // Apply format enforcement if needed
    if (enforce_format && selectedApproach === 'CoD') {
      reasoningSteps = formatEnforcer.enforceWordLimit(reasoningSteps, wordLimit);
    }
    
    // Calculate execution time
    const executionTime = Date.now() - startTime;
    
    // Estimate token count (rough approximation)
    const tokenCount = Math.ceil(fullText.length / 4);
    
    // Record analytics
    analyticsDb.addRecord({
      problem_id: problem.substring(0, 20),
      problem_text: problem,
      domain,
      approach: selectedApproach,
      word_limit: wordLimit,
      tokens_used: tokenCount,
      execution_time_ms: executionTime,
      reasoning_steps: reasoningSteps,
      answer: finalAnswer
    });
    
    // Return result
    return {
      approach: selectedApproach,
      reasoning_steps: reasoningSteps,
      final_answer: finalAnswer,
      token_count: tokenCount,
      word_limit: wordLimit,
      complexity: complexity,
      execution_time_ms: executionTime
    };
  }