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AzDeltaQQ

MCP Advanced Reasoning Server

by AzDeltaQQ

beam_search_reasoning

Perform beam search reasoning to explore multiple solution paths for complex problems, maintaining top candidate sequences for step-by-step analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe problem or query to reason about
thoughtYesCurrent reasoning step
thoughtNumberYesCurrent step number
totalThoughtsYesTotal expected steps
nextThoughtNeededYesWhether another step is needed
beamWidthNoNumber of top paths to maintain (n-sampling)

Implementation Reference

  • The async handler function implementing the beam_search_reasoning tool logic: validates inputs, simulates beam search reasoning step, generates next thought placeholder, and returns structured JSON response.
    async ({ prompt, thought, thoughtNumber, totalThoughts, nextThoughtNeeded, beamWidth }) => {
      try {
        // Validate parameters
        if (!prompt) {
          throw new ValidationError("Prompt is required");
        }
        
        if (!thought) {
          throw new ValidationError("Current thought is required");
        }
        
        // In a real implementation, this would connect to an external Beam Search algorithm
        // For now, we'll simulate the reasoning process
        
        // Simulated next thought generation based on Beam Search
        let nextThought = "";
        
        if (nextThoughtNeeded) {
          // Logic for generating next thought would go here
          // For now, we'll return a simple placeholder
          nextThought = `Beam Search Reasoning (Step ${thoughtNumber + 1}/${totalThoughts}): ` +
                        `Considering ${beamWidth} alternative paths from "${thought.slice(0, 50)}...", ` +
                        `the most promising direction is... ` +
                        `[This would be actual Beam Search-based reasoning content]`;
        }
        
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                strategy: "beam_search",
                originalPrompt: prompt,
                currentThought: thought,
                thoughtNumber: thoughtNumber,
                totalThoughts: totalThoughts,
                nextThought: nextThought,
                complete: !nextThoughtNeeded || thoughtNumber >= totalThoughts
              }, null, 2)
            }
          ]
        };
      } catch (error) {
        if (error instanceof ValidationError) {
          throw error;
        } else {
          throw new ReasoningError(`Beam Search reasoning failed: ${error instanceof Error ? error.message : String(error)}`);
        }
      }
    }
  • Zod schema defining input parameters for the beam_search_reasoning tool: prompt, thought, thoughtNumber, totalThoughts, nextThoughtNeeded, and beamWidth.
    {
      prompt: z.string().describe("The problem or query to reason about"),
      thought: z.string().describe("Current reasoning step"),
      thoughtNumber: z.number().int().min(1).describe("Current step number"),
      totalThoughts: z.number().int().min(1).describe("Total expected steps"),
      nextThoughtNeeded: z.boolean().describe("Whether another step is needed"),
      beamWidth: z.number().int().min(1).max(10).default(3).describe("Number of top paths to maintain (n-sampling)")
    },
  • Local registration of the beam_search_reasoning tool within registerReasoningTools using server.tool(), including schema and inline handler.
    server.tool(
      "beam_search_reasoning",
      {
        prompt: z.string().describe("The problem or query to reason about"),
        thought: z.string().describe("Current reasoning step"),
        thoughtNumber: z.number().int().min(1).describe("Current step number"),
        totalThoughts: z.number().int().min(1).describe("Total expected steps"),
        nextThoughtNeeded: z.boolean().describe("Whether another step is needed"),
        beamWidth: z.number().int().min(1).max(10).default(3).describe("Number of top paths to maintain (n-sampling)")
      },
      async ({ prompt, thought, thoughtNumber, totalThoughts, nextThoughtNeeded, beamWidth }) => {
        try {
          // Validate parameters
          if (!prompt) {
            throw new ValidationError("Prompt is required");
          }
          
          if (!thought) {
            throw new ValidationError("Current thought is required");
          }
          
          // In a real implementation, this would connect to an external Beam Search algorithm
          // For now, we'll simulate the reasoning process
          
          // Simulated next thought generation based on Beam Search
          let nextThought = "";
          
          if (nextThoughtNeeded) {
            // Logic for generating next thought would go here
            // For now, we'll return a simple placeholder
            nextThought = `Beam Search Reasoning (Step ${thoughtNumber + 1}/${totalThoughts}): ` +
                          `Considering ${beamWidth} alternative paths from "${thought.slice(0, 50)}...", ` +
                          `the most promising direction is... ` +
                          `[This would be actual Beam Search-based reasoning content]`;
          }
          
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify({
                  strategy: "beam_search",
                  originalPrompt: prompt,
                  currentThought: thought,
                  thoughtNumber: thoughtNumber,
                  totalThoughts: totalThoughts,
                  nextThought: nextThought,
                  complete: !nextThoughtNeeded || thoughtNumber >= totalThoughts
                }, null, 2)
              }
            ]
          };
        } catch (error) {
          if (error instanceof ValidationError) {
            throw error;
          } else {
            throw new ReasoningError(`Beam Search reasoning failed: ${error instanceof Error ? error.message : String(error)}`);
          }
        }
      }
    );
  • src/index.ts:22-22 (registration)
    Top-level registration call to registerReasoningTools(server) in the main MCP server setup, which includes the beam_search_reasoning tool.
    registerReasoningTools(server);
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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