MCP Advanced Reasoning Server

Implementation Reference

• src/tools/reasoning-tools.ts:24-73 (handler)

  The handler function that implements the core logic of the mcts_reasoning tool. It validates inputs, simulates MCTS reasoning (placeholder), generates next thought if needed, and returns structured JSON response.
  async ({ prompt, thought, thoughtNumber, totalThoughts, nextThoughtNeeded, numSimulations }) => { 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 MCTS algorithm // For now, we'll simulate the reasoning process // Simulated next thought generation based on MCTS let nextThought = ""; if (nextThoughtNeeded) { // Logic for generating next thought would go here // For now, we'll return a simple placeholder nextThought = `MCTS Reasoning (Step ${thoughtNumber + 1}/${totalThoughts}): ` + `Based on previous analysis "${thought.slice(0, 50)}...", ` + `further exploration with ${numSimulations} simulations suggests... ` + `[This would be actual MCTS-based reasoning content]`; } return { content: [ { type: "text", text: JSON.stringify({ strategy: "mcts", 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(`MCTS reasoning failed: ${error instanceof Error ? error.message : String(error)}`); } } }
• src/tools/reasoning-tools.ts:16-22 (schema)

  Zod schema defining the input parameters for the mcts_reasoning tool, including prompt, current thought, step numbers, and MCTS-specific parameters.
  { 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"), numSimulations: z.number().int().min(1).max(150).default(50).describe("Number of MCTS simulations to run")
• src/tools/reasoning-tools.ts:14-74 (registration)

  The server.tool call that registers the mcts_reasoning tool with its input schema and handler function on the MCP server.
  server.tool( "mcts_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"), numSimulations: z.number().int().min(1).max(150).default(50).describe("Number of MCTS simulations to run") }, async ({ prompt, thought, thoughtNumber, totalThoughts, nextThoughtNeeded, numSimulations }) => { 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 MCTS algorithm // For now, we'll simulate the reasoning process // Simulated next thought generation based on MCTS let nextThought = ""; if (nextThoughtNeeded) { // Logic for generating next thought would go here // For now, we'll return a simple placeholder nextThought = `MCTS Reasoning (Step ${thoughtNumber + 1}/${totalThoughts}): ` + `Based on previous analysis "${thought.slice(0, 50)}...", ` + `further exploration with ${numSimulations} simulations suggests... ` + `[This would be actual MCTS-based reasoning content]`; } return { content: [ { type: "text", text: JSON.stringify({ strategy: "mcts", 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(`MCTS reasoning failed: ${error instanceof Error ? error.message : String(error)}`); } } } );
• src/index.ts:22-22 (registration)

  Invocation of registerReasoningTools which includes registration of mcts_reasoning among other reasoning tools.
  registerReasoningTools(server);
• src/tools/reasoning-tools.ts:12-250 (helper)

  Helper function that registers all reasoning tools, including mcts_reasoning, on the MCP server.
  export function registerReasoningTools(server: McpServer) { // Monte Carlo Tree Search (MCTS) tool server.tool( "mcts_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"), numSimulations: z.number().int().min(1).max(150).default(50).describe("Number of MCTS simulations to run") }, async ({ prompt, thought, thoughtNumber, totalThoughts, nextThoughtNeeded, numSimulations }) => { 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 MCTS algorithm // For now, we'll simulate the reasoning process // Simulated next thought generation based on MCTS let nextThought = ""; if (nextThoughtNeeded) { // Logic for generating next thought would go here // For now, we'll return a simple placeholder nextThought = `MCTS Reasoning (Step ${thoughtNumber + 1}/${totalThoughts}): ` + `Based on previous analysis "${thought.slice(0, 50)}...", ` + `further exploration with ${numSimulations} simulations suggests... ` + `[This would be actual MCTS-based reasoning content]`; } return { content: [ { type: "text", text: JSON.stringify({ strategy: "mcts", 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(`MCTS reasoning failed: ${error instanceof Error ? error.message : String(error)}`); } } } ); // Beam Search tool 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: ${error instanceof Error ? error.message : String(error)}`); } } } ); // R1 Transformer-based reasoning tool server.tool( "r1_reasoning", { prompt: z.string().describe("The problem or query to reason about") }, async ({ prompt }) => { try { // Validate parameters if (!prompt) { throw new ValidationError("Prompt is required"); } // In a real implementation, this would connect to an external R1 reasoning system // For now, we'll simulate the reasoning process // Simulated reasoning output const reasoning = `R1 Reasoning Analysis:\n\n` + `For the prompt: "${prompt.slice(0, 100)}...", the analysis is:\n\n` + `1. Initial problem parsing: [Simulated R1 analysis]\n` + `2. Key observation: [Simulated R1 analysis]\n` + `3. Proposed solution approach: [Simulated R1 analysis]\n` + `4. Implementation details: [Simulated R1 analysis]\n` + `5. Verification and testing: [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: prompt, reasoning: reasoning, complete: true }, null, 2) } ] }; } catch (error) { if (error instanceof ValidationError) { throw error; } else { throw new ReasoningError(`R1 reasoning failed: ${error instanceof Error ? error.message : String(error)}`); } } } ); // Hybrid Transformer reasoning tool server.tool( "hybrid_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"), numSimulations: z.number().int().min(1).max(150).default(50).describe("Number of MCTS simulations to run") }, async ({ prompt, thought, thoughtNumber, totalThoughts, nextThoughtNeeded, numSimulations }) => { 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 a hybrid transformer+MCTS system // For now, we'll simulate the reasoning process // Simulated next thought generation based on hybrid approach let nextThought = ""; if (nextThoughtNeeded) { // Logic for generating next thought would go here // For now, we'll return a simple placeholder nextThought = `Hybrid Reasoning (Step ${thoughtNumber + 1}/${totalThoughts}): ` + `Combining transformer analysis with ${numSimulations} MCTS simulations on "${thought.slice(0, 50)}...", ` + `the enhanced analysis suggests... ` + `[This would be actual Hybrid Transformer+MCTS reasoning content]`; } return { content: [ { type: "text", text: JSON.stringify({ strategy: "hybrid_transformer_mcts", 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(`Hybrid reasoning failed: ${error instanceof Error ? error.message : String(error)}`); } } } ); }