@makingchatbots/genesys-cloud-mcp-server/dist/tools/conversationSentiment/conversationSentiment.js

A Model Context Protocol (MCP) server exposing Genesys Cloud tools for LLMs, including sentiment analysis, conversation search, topic detection and more.

import { z } from "zod";
import { createTool } from "../utils/createTool.js";
import { isUnauthorisedError } from "../utils/genesys/isUnauthorisedError.js";
import { errorResult } from "../utils/errorResult.js";
import { isConversationNotFoundError } from "./isConversationNotFoundError.js";
import { interpretSentiment } from "./interpretSentiment.js";
const paramsSchema = z.object({
    conversationIds: z
        .array(z
        .string()
        .uuid()
        .describe("A UUID for a conversation. (e.g., 00000000-0000-0000-0000-000000000000)"))
        .min(1)
        .max(100)
        .describe("A list of up to 100 conversation IDs to retrieve sentiment for"),
});
export const conversationSentiment = ({ speechTextAnalyticsApi }) => createTool({
    schema: {
        name: "conversation_sentiment",
        description: "Retrieves sentiment analysis scores for one or more conversations. Sentiment is evaluated based on customer phrases, categorized as positive, neutral, or negative. The result includes both a numeric sentiment score (-100 to 100) and an interpreted sentiment label.",
        paramsSchema,
    },
    call: async ({ conversationIds }) => {
        const conversations = [];
        conversations.push(...(await Promise.allSettled(conversationIds.map((id) => speechTextAnalyticsApi.getSpeechandtextanalyticsConversation(id)))));
        const output = [];
        for (const convo of conversations) {
            if (convo.status === "fulfilled") {
                const id = convo.value.conversation?.id;
                const score = convo.value.sentimentScore;
                if (id === undefined || score === undefined)
                    continue;
                const scaledScore = Math.round(score * 100);
                output.push(`• Conversation ID: ${id}\n  • Sentiment Score: ${String(scaledScore)} (${interpretSentiment(scaledScore)})`);
            }
            else {
                const result = isConversationNotFoundError(convo.reason);
                if (result.isResourceNotFoundError && result.conversationId) {
                    output.push(`• Conversation ID: ${result.conversationId}\n  • Error: Conversation not found`);
                }
                else if (isUnauthorisedError(convo.reason)) {
                    return errorResult("Failed to retrieve sentiment analysis: Unauthorised access. Please check API credentials or permissions.");
                }
                else {
                    // Ignore conversation
                }
            }
        }
        return {
            content: [
                {
                    type: "text",
                    text: output.length > 0
                        ? [
                            `Sentiment results for ${String(output.length)} conversation(s):`,
                            ...output,
                        ].join("\n\n")
                        : "No sentiment data found for the given conversation IDs.",
                },
            ],
        };
    },
});