MCP Advanced Reasoning Server
by AzDeltaQQ
Verified
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.registerReasoningTools = registerReasoningTools;
const errors_1 = require("../utils/errors");
const zod_1 = require("zod");
// Constants
const RESOURCE_NAMESPACE = "cursor://reasoning";
/**
* Register all reasoning tools with the MCP server
* @param server MCP server instance
*/
function registerReasoningTools(server) {
// Monte Carlo Tree Search (MCTS) tool
server.tool("mcts_reasoning", {
prompt: zod_1.z.string().describe("The problem or query to reason about"),
thought: zod_1.z.string().describe("Current reasoning step"),
thoughtNumber: zod_1.z.number().int().min(1).describe("Current step number"),
totalThoughts: zod_1.z.number().int().min(1).describe("Total expected steps"),
nextThoughtNeeded: zod_1.z.boolean().describe("Whether another step is needed"),
numSimulations: zod_1.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 errors_1.ValidationError("Prompt is required");
}
if (!thought) {
throw new errors_1.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 errors_1.ValidationError) {
throw error;
}
else {
throw new errors_1.ReasoningError(`MCTS reasoning failed: ${error instanceof Error ? error.message : String(error)}`);
}
}
});
// Beam Search tool
server.tool("beam_search_reasoning", {
prompt: zod_1.z.string().describe("The problem or query to reason about"),
thought: zod_1.z.string().describe("Current reasoning step"),
thoughtNumber: zod_1.z.number().int().min(1).describe("Current step number"),
totalThoughts: zod_1.z.number().int().min(1).describe("Total expected steps"),
nextThoughtNeeded: zod_1.z.boolean().describe("Whether another step is needed"),
beamWidth: zod_1.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 errors_1.ValidationError("Prompt is required");
}
if (!thought) {
throw new errors_1.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 errors_1.ValidationError) {
throw error;
}
else {
throw new errors_1.ReasoningError(`Beam Search reasoning failed: ${error instanceof Error ? error.message : String(error)}`);
}
}
});
// R1 Transformer-based reasoning tool
server.tool("r1_reasoning", {
prompt: zod_1.z.string().describe("The problem or query to reason about")
}, async ({ prompt }) => {
try {
// Validate parameters
if (!prompt) {
throw new errors_1.ValidationError("Prompt is required");
}
// In a real implementation, this would connect to an external R1 reasoning system
// For now, we'll simulate the reasoning process
// Simulated reasoning output
const reasoning = `R1 Reasoning Analysis:\n\n` +
`For the prompt: "${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 errors_1.ValidationError) {
throw error;
}
else {
throw new errors_1.ReasoningError(`R1 reasoning failed: ${error instanceof Error ? error.message : String(error)}`);
}
}
});
// Hybrid Transformer reasoning tool
server.tool("hybrid_reasoning", {
prompt: zod_1.z.string().describe("The problem or query to reason about"),
thought: zod_1.z.string().describe("Current reasoning step"),
thoughtNumber: zod_1.z.number().int().min(1).describe("Current step number"),
totalThoughts: zod_1.z.number().int().min(1).describe("Total expected steps"),
nextThoughtNeeded: zod_1.z.boolean().describe("Whether another step is needed"),
numSimulations: zod_1.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 errors_1.ValidationError("Prompt is required");
}
if (!thought) {
throw new errors_1.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 errors_1.ValidationError) {
throw error;
}
else {
throw new errors_1.ReasoningError(`Hybrid reasoning failed: ${error instanceof Error ? error.message : String(error)}`);
}
}
});
}