Skip to main content
Glama
mako10k

MCP-Confirm

by mako10k

clarify_intent

Clarify ambiguous user requests by identifying unclear elements and presenting specific interpretation options for user selection.

Instructions

Ask user to clarify their intent when the request is ambiguous or could be interpreted multiple ways

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_summaryYesSummary of what the AI understood from the user's request
ambiguityYesDescription of what is unclear or ambiguous
optionsNoPossible interpretations or options for the user to choose from

Implementation Reference

  • The primary handler function that implements the execution logic for the 'clarify_intent' tool. It parses input arguments, builds a user-facing message and dynamic elicitation schema (including options if provided), sends an elicitation request to the user, and returns the response or error.
    private async handleClarifyIntent(args: Record<string, unknown>) { const request_summary = typeof args.request_summary === "string" ? args.request_summary : "Unknown request"; const ambiguity = typeof args.ambiguity === "string" ? args.ambiguity : "Unknown ambiguity"; const options = Array.isArray(args.options) ? args.options : undefined; let message = `I need to clarify your intent:\n\n**My understanding**: ${request_summary}\n\n**What's unclear**: ${ambiguity}`; const schema: ElicitationSchema = { type: "object", properties: {}, required: ["clarification"], }; // Add selected_option FIRST if options exist (for better UX - selection before free text) if (options && options.length > 0) { message += `\n\n**Options**:\n${options.map((opt: unknown, i: number) => `${i + 1}. ${String(opt)}`).join("\n")}`; schema.properties.selected_option = { type: "string", title: "Select Option", description: "Which option best matches your intent?", enum: options.map((opt) => String(opt)), }; } // Add clarification field AFTER options (better UX - free text input comes after selection) schema.properties.clarification = { type: "string", title: "Additional clarification", description: "Please provide any additional details or explanation", }; const elicitationParams: ElicitationParams = { message, requestedSchema: schema, }; try { const response = await this.sendElicitationRequest(elicitationParams); if (response.action === "accept") { return { content: [ { type: "text", text: `User clarification:\n${JSON.stringify(response.content, null, 2)}`, }, ], }; } else { return { content: [ { type: "text", text: `User ${response.action}ed the clarification request.`, }, ], }; } } catch (error) { return this.createErrorResponse( `Clarification request failed: ${error instanceof Error ? error.message : String(error)}` ); } }
  • src/index.ts:288-317 (registration)
    The factory function that creates and returns the Tool object for 'clarify_intent', including its name, description, and inputSchema definition.
    private createClarifyIntentTool(): Tool { return { name: "clarify_intent", description: "Ask user to clarify their intent when the request is ambiguous or could be interpreted multiple ways", inputSchema: { type: "object", properties: { request_summary: { type: "string", description: "Summary of what the AI understood from the user's request", }, ambiguity: { type: "string", description: "Description of what is unclear or ambiguous", }, options: { type: "array", items: { type: "string", }, description: "Possible interpretations or options for the user to choose from", }, }, required: ["request_summary", "ambiguity"], }, }; }
  • The input schema defining the expected parameters for the clarify_intent tool: required request_summary and ambiguity, optional options array.
    inputSchema: { type: "object", properties: { request_summary: { type: "string", description: "Summary of what the AI understood from the user's request", }, ambiguity: { type: "string", description: "Description of what is unclear or ambiguous", }, options: { type: "array", items: { type: "string", }, description: "Possible interpretations or options for the user to choose from", }, }, required: ["request_summary", "ambiguity"], },
  • src/index.ts:522-523 (registration)
    The dispatch switch case in executeToolCall that routes calls to the 'clarify_intent' tool to its handler function.
    case "clarify_intent": return await this.handleClarifyIntent(args);
  • src/index.ts:231-242 (registration)
    The getToolDefinitions method that registers clarify_intent by calling createClarifyIntentTool() and including it in the list of available tools.
    private getToolDefinitions(): Tool[] { return [ this.createAskYesNoTool(), this.createConfirmActionTool(), this.createClarifyIntentTool(), this.createVerifyUnderstandingTool(), this.createCollectRatingTool(), this.createElicitCustomTool(), this.createSearchLogsTool(), this.createAnalyzeLogsTool(), ]; }

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mako10k/mcp-confirm'

If you have feedback or need assistance with the MCP directory API, please join our Discord server