Stochastic Thinking MCP Server

Instructions

Implementation Reference

• index.js:73-119 (handler)

  Core handler function that executes the stochasticalgorithm tool logic: validates input, logs formatted output, generates algorithm-specific one-line summary, and returns structured JSON response.

  processAlgorithm(input) {
      try {
          const validatedInput = this.validateStochasticData(input);
          const formattedOutput = this.formatOutput(validatedInput);
          console.error(formattedOutput);
          let summary = '';
          switch (validatedInput.algorithm) {
              case 'mdp':
                  summary = this.mdpOneLineSummary(validatedInput.parameters);
                  break;
              case 'mcts':
                  summary = this.mctsOneLineSummary(validatedInput.parameters);
                  break;
              case 'bandit':
                  summary = this.banditOneLineSummary(validatedInput.parameters);
                  break;
              case 'bayesian':
                  summary = this.bayesianOneLineSummary(validatedInput.parameters);
                  break;
              case 'hmm':
                  summary = this.hmmOneLineSummary(validatedInput.parameters);
                  break;
          }
          return {
              content: [{
                  type: "text",
                  text: JSON.stringify({
                      algorithm: validatedInput.algorithm,
                      status: 'success',
                      summary,
                      hasResult: !!validatedInput.result
                  }, null, 2)
              }]
          };
      } catch (error) {
          return {
              content: [{
                  type: "text",
                  text: JSON.stringify({
                      error: error instanceof Error ? error.message : String(error),
                      status: 'failed'
                  }, null, 2)
              }],
              isError: true
          };
      }
  }

• index.js:123-156 (schema)

  Tool schema defining name, description, and input validation schema for stochasticalgorithm.

  const STOCHASTIC_TOOL = {
      name: "stochasticalgorithm",
      description: `A tool for applying stochastic algorithms to decision-making problems.
  Supports various algorithms including:
  - Markov Decision Processes (MDPs): Optimize policies over long sequences of decisions
  - Monte Carlo Tree Search (MCTS): Simulate future action sequences for large decision spaces
  - Multi-Armed Bandit: Balance exploration vs exploitation in action selection
  - Bayesian Optimization: Optimize decisions with probabilistic inference
  - Hidden Markov Models (HMMs): Infer latent states affecting decision outcomes
  
  Each algorithm provides a systematic approach to handling uncertainty in decision-making.`,
      inputSchema: {
          type: "object",
          properties: {
              algorithm: {
                  type: "string",
                  enum: [
                      "mdp",
                      "mcts",
                      "bandit",
                      "bayesian",
                      "hmm"
                  ]
              },
              problem: { type: "string" },
              parameters: {
                  type: "object",
                  additionalProperties: true
              },
              result: { type: "string" }
          },
          required: ["algorithm", "problem", "parameters"]
      }
  };

• index.js:159-169 (registration)

  Server initialization and registration of the stochasticalgorithm tool in capabilities.

  const stochasticServer = new StochasticServer();
  const server = new Server({
      name: "stochastic-thinking-server",
      version: "0.1.0",
  }, {
      capabilities: {
          tools: {
              stochasticalgorithm: STOCHASTIC_TOOL
          },
      },
  });

• index.js:176-183 (registration)

  Request handler registration for CallToolRequestSchema, dispatching stochasticalgorithm calls to the handler.

  server.setRequestHandler(CallToolRequestSchema, async (request) => {
      switch (request.params.name) {
          case "stochasticalgorithm":
              return stochasticServer.processAlgorithm(request.params.arguments);
          default:
              throw new McpError(ErrorCode.MethodNotFound, `Unknown tool: ${request.params.name}`);
      }
  });

• index.js:13-30 (helper)

  Helper function to validate and normalize input data for the stochastic algorithm tool.

  validateStochasticData(input) {
      const data = input;
      if (!data.algorithm || typeof data.algorithm !== 'string') {
          throw new Error('Invalid algorithm: must be a string');
      }
      if (!data.problem || typeof data.problem !== 'string') {
          throw new Error('Invalid problem: must be a string');
      }
      if (!data.parameters || typeof data.parameters !== 'object') {
          throw new Error('Invalid parameters: must be an object');
      }
      return {
          algorithm: data.algorithm,
          problem: data.problem,
          parameters: data.parameters,
          result: typeof data.result === 'string' ? data.result : undefined
      };
  }