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AzDeltaQQ

MCP Advanced Reasoning Server

by AzDeltaQQ

reason_r1

Solve complex problems and tasks using R1 Transformer reasoning capabilities to analyze and process queries for enhanced decision-making.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe problem or task to reason about using R1 Transformer

Implementation Reference

  • Registers the "reason_r1" MCP tool on the server, including input schema and complete handler implementation.
    server.tool(
      "reason_r1",
      {
        query: z.string().describe("The problem or task to reason about using R1 Transformer")
      },
      async ({ query }) => {
        try {
          // Generate R1 reasoning response
          const reasoning = `R1 Reasoning Analysis:\n\n` +
                            `For the problem: "${query}", my analysis is:\n\n` +
                            `1. Initial problem understanding: [Simulated R1 analysis]\n` +
                            `2. Key aspects to consider: [Simulated R1 analysis]\n` +
                            `3. Potential solutions: [Simulated R1 analysis]\n` +
                            `4. Recommended approach: [Simulated R1 analysis]\n` +
                            `5. Implementation considerations: [Simulated R1 analysis]\n\n` +
                            `[This would be actual R1 Transformer-based reasoning content]`;
          
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify({
                  strategy: "r1_transformer",
                  originalPrompt: query,
                  reasoning: reasoning,
                  complete: true
                }, null, 2)
              }
            ]
          };
        } catch (error) {
          throw new ReasoningError(`R1 reasoning command failed: ${error instanceof Error ? error.message : String(error)}`);
        }
      }
    );
  • The handler function for "reason_r1" that generates a simulated structured R1 Transformer reasoning response based on the input query.
    async ({ query }) => {
      try {
        // Generate R1 reasoning response
        const reasoning = `R1 Reasoning Analysis:\n\n` +
                          `For the problem: "${query}", my analysis is:\n\n` +
                          `1. Initial problem understanding: [Simulated R1 analysis]\n` +
                          `2. Key aspects to consider: [Simulated R1 analysis]\n` +
                          `3. Potential solutions: [Simulated R1 analysis]\n` +
                          `4. Recommended approach: [Simulated R1 analysis]\n` +
                          `5. Implementation considerations: [Simulated R1 analysis]\n\n` +
                          `[This would be actual R1 Transformer-based reasoning content]`;
        
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                strategy: "r1_transformer",
                originalPrompt: query,
                reasoning: reasoning,
                complete: true
              }, null, 2)
            }
          ]
        };
      } catch (error) {
        throw new ReasoningError(`R1 reasoning command failed: ${error instanceof Error ? error.message : String(error)}`);
      }
    }
  • Zod input schema for the "reason_r1" tool, defining a single 'query' string parameter.
    {
      query: z.string().describe("The problem or task to reason about using R1 Transformer")
  • src/index.ts:23-23 (registration)
    Top-level registration call to registerCommandWrappers, which includes the "reason_r1" tool.
    registerCommandWrappers(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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