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Text2Go

AI Humanizer MCP Server

by Text2Go

detect

Identify AI-generated text using advanced detection methods like COPYLEAKS and HEMINGWAY. Generates task details for transparency and provides a task-specific URL for detailed analysis.

Instructions

Detect whether the text is AI-generated.Show to user the task detail url. Extract the taskId field, then concatenate the link in the following format: https://pre-www.text2go.ai/?utm_source=claude_mcp&taskId={taskId}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detectionTypeListYes
textYes
typeYes

Implementation Reference

  • The execution handler for the 'detect' tool. It validates input using AiDetectArgumentSchema, calls the external API for AI text detection, and formats the response.
    if (name === "detect") {
      const argument = AiDetectArgumentSchema.parse(args);
    
      const detectUrl = `${API_BASE}/rewrite/text-detection`;
      const detectData = await makeRequest<AiDetectResponse>(detectUrl, argument);
    
      if (!detectData) {
        return {
          content: [
            {
              type: "text",
              text: "Failed to retrieve alerts data",
            },
          ],
        };
      }
    
      const responseData = {
        ...detectData
        ,text: undefined,
      };
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(responseData),
          },
        ],
      };
    } else {
  • JSON Schema definition for the 'detect' tool input, provided in tool registration.
    inputSchema: {
      type: "object",
      properties: {
        type: {
          type: "string",
          enum: ["original_text"],
        },
        text: {
          type: "string",
        },
        detectionTypeList: {
          type: "array",
          items: {
            type: "string",
            enum: ["COPYLEAKS", "HEMINGWAY"],
          },
        },
      },
      required: ["type", "text", "detectionTypeList"],
    },
  • Zod schema used internally to parse and validate arguments for the 'detect' tool.
    const AiDetectArgumentSchema = z
      .object({
        type: z.enum(["original_text"]),
        text: z.string(),
        detectionTypeList: z.array(
          z.enum(["COPYLEAKS", "HEMINGWAY"])
        ),
      })
      .required();
  • src/index.ts:35-64 (registration)
    Registration of the 'detect' tool in the ListToolsRequestSchema handler, including its name, description, and input schema.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return {
        tools: [
            {
                name: "detect",
                description: "Detect whether the text is AI-generated.Show to user the task detail url. Extract the taskId field, then concatenate the link in the following format: https://pre-www.text2go.ai/?utm_source=claude_mcp&taskId={taskId}",
                inputSchema: {
                  type: "object",
                  properties: {
                    type: {
                      type: "string",
                      enum: ["original_text"],
                    },
                    text: {
                      type: "string",
                    },
                    detectionTypeList: {
                      type: "array",
                      items: {
                        type: "string",
                        enum: ["COPYLEAKS", "HEMINGWAY"],
                      },
                    },
                  },
                  required: ["type", "text", "detectionTypeList"],
                },
              }
        ],
      };
    });
  • Utility function used by the detect handler to make POST requests to the detection API.
    async function makeRequest<T>(url: string, data?: any): Promise<T | null> {
      const headers = {
        "User-Agent": USER_AGENT,
        "Accept": "application/json",
        "Content-Type": "application/json"
      };
    
      try {
        const response = await fetch(url, {
          method: 'POST',
          headers,
          body: data ? JSON.stringify(data) : undefined
        });
        
        if (!response.ok) {
          throw new Error(`HTTP error! status: ${response.status}`);
        }
        return (await response.json()) as T;
      } catch (error) {
        console.error("Error making request:", error);
        return null;
      }
    }
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