Prompt Cleaner MCP Server

Instructions

Implementation Reference

• src/tools.ts:56-74 (registration)

  Registration of the 'normalize-prompt' tool in the listTools() function, including its description and input schema (identical to 'cleaner').

  {
    name: "normalize-prompt",
    description:
      "Alias of cleaner. Keywords: normalize, restructure, clarify, tighten, format, preflight. Same input/output schema as 'cleaner'.",
    inputSchema: {
      type: "object",
      properties: {
        prompt: { type: "string", description: "Raw user prompt" },
        mode: {
          type: "string",
          enum: ["code", "general"],
          description:
            "Retouching mode; default 'general'. Use 'code' only for code-related prompts.",
        },
        temperature: { type: "number", description: "Sampling temperature (0-2); default 0.2" },
      },
      required: ["prompt"],
    },
  },

• src/tools.ts:92-105 (handler)

  Dispatch handler in callTool() for 'normalize-prompt' (shared with 'cleaner' and 'sanitize-text'), which validates input using RetouchInput schema, calls retouchPrompt, validates output, logs, and returns JSON.

  case "cleaner":
  case "sanitize-text":
  case "normalize-prompt": {
    const parsed = RetouchInput.parse(args);
    const result = await retouchPrompt(parsed);
    const safe = RetouchOutput.parse(result);
    logger.info("retouch.prompt", {
      elapsed_ms: Date.now() - start,
      input_len: parsed.prompt.length,
      preview: logger.preview(parsed.prompt),
      request_id: parsed.requestId,
    });
    return jsonContent(safe);
  }

• src/cleaner.ts:83-180 (handler)

  Core implementation of prompt normalization in retouchPrompt(): loads system prompt from file, calls LLM (chatCompletions) with retry logic for JSON output, extracts/parses JSON, applies redaction, validates with RetouchOutput schema, and logs extensively.

  export async function retouchPrompt(input: RetouchInputT): Promise<RetouchOutputT> {
    const start = Date.now();
    const system = await loadCleanerSystemPrompt();
    const baseTemperature = input.temperature ?? 0;
  
    const userBody = `MODE: ${input.mode || "general"}\nRAW_PROMPT:\n${input.prompt}`;
    const sys = system;
  
    class CleanerNonJsonError extends Error {
      constructor(message = "Cleaner returned non-JSON") {
        super(message);
        this.name = "CleanerNonJsonError";
      }
    }
  
    // Retry loop for content-level non-JSON responses
    const maxAttempts = Math.max(1, 1 + (config.contentMaxRetries ?? 0));
    let lastErr: Error | undefined;
    for (let attempt = 1; attempt <= maxAttempts; attempt++) {
      // Escalate on retries: enforce temperature 0 and stricter system instructions
      const strictSuffix =
        attempt > 1
          ? "\n\nSTRICT OUTPUT MODE: Respond with EXACTLY ONE JSON object and nothing else. No prose. No code fences. No prefix/suffix."
          : "";
      const sysAttempt = sys + strictSuffix;
      const tempAttempt = attempt > 1 ? 0 : baseTemperature;
  
      const response = await chatCompletions(
        {
          model: config.model,
          temperature: tempAttempt,
          max_tokens: 600,
          messages: [
            { role: "system", content: sysAttempt },
            { role: "user", content: userBody },
          ],
        },
        { requestId: input.requestId },
      );
  
      const content = response.choices?.[0]?.message?.content ?? "";
      const initial = redactSecrets(content);
      const redactedText = initial.text;
      try {
        const obj = extractFirstJsonObject(redactedText);
        const parsed = RetouchOutput.safeParse(obj);
        if (!parsed.success) {
          throw new Error("shape-error");
        }
  
        const { value, redactions } = ensureNoSecretsInObject(parsed.data);
        const totalRedactions = initial.count + redactions;
        const result: RetouchOutputT = {
          ...value,
          redactions:
            totalRedactions > 0 ? Array(totalRedactions).fill("[REDACTED]") : value.redactions,
        };
  
        logger.info("retouch.prompt", {
          elapsed_ms: Date.now() - start,
          input_len: input.prompt.length,
          preview: logger.preview(input.prompt),
          request_id: input.requestId,
          attempts: attempt,
          outcome: "ok",
        });
  
        return result;
      } catch (e: any) {
        lastErr = new CleanerNonJsonError("Cleaner returned non-JSON");
        if (attempt < maxAttempts) {
          const base = config.backoffMs ?? 250;
          const jitter = config.backoffJitter ?? 0.2;
          const exp = Math.pow(2, attempt - 1);
          const rand = 1 + (Math.random() * 2 - 1) * jitter; // 1 +/- jitter
          const delay = Math.max(0, Math.floor(base * exp * rand));
          logger.warn("retouch.retry", {
            request_id: input.requestId,
            attempt,
            delay_ms: delay,
            reason: "non-json",
          });
          await new Promise((r) => setTimeout(r, delay));
          continue;
        }
      }
    }
    logger.info("retouch.prompt", {
      elapsed_ms: Date.now() - start,
      input_len: input.prompt.length,
      preview: logger.preview(input.prompt),
      request_id: input.requestId,
      attempts: maxAttempts,
      outcome: "error",
      reason: "non-json",
    });
    throw lastErr ?? new CleanerNonJsonError("Cleaner returned non-JSON");
  }

• src/shapes.ts:5-18 (schema)

  Zod schemas for RetouchInput and RetouchOutput used for validation in the normalize-prompt (cleaner) tool handler.

  export const RetouchInput = z.object({
    prompt: z.string().min(1),
    mode: z.enum(["code", "general"]).optional(),
    temperature: z.number().min(0).max(2).optional(),
    requestId: z.string().uuid().optional(),
  });
  
  export const RetouchOutput = z.object({
    retouched: z.string().min(1),
    notes: z.array(z.string()).optional(),
    openQuestions: z.array(z.string()).optional(),
    risks: z.array(z.string()).optional(),
    redactions: z.array(z.literal("[REDACTED]")).optional(),
  });