import { randomUUID } from "node:crypto";
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { InMemoryTransport } from "@modelcontextprotocol/sdk/inMemory.js";
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import type { McpError } from "@modelcontextprotocol/sdk/types.js";
import type { MockedObjectDeep } from "@vitest/spy";
import { beforeEach, describe, expect, test, vi } from "vitest";
import {
conversationTopics,
type ToolDependencies,
} from "./conversationTopics.js";
describe("Conversation Topics Tool", () => {
let toolDeps: MockedObjectDeep<ToolDependencies>;
let client: Client;
let toolName: string;
beforeEach(async () => {
toolDeps = {
speechTextAnalyticsApi: {
getSpeechandtextanalyticsTopics: vi.fn(),
},
analyticsApi: {
getAnalyticsConversationDetails: vi.fn(),
postAnalyticsTranscriptsAggregatesQuery: vi.fn(),
},
};
const toolDefinition = conversationTopics(toolDeps);
toolName = toolDefinition.schema.name;
const server = new McpServer({ name: "TestServer", version: "test" });
server.tool(
toolDefinition.schema.name,
toolDefinition.schema.description,
toolDefinition.schema.paramsSchema.shape,
toolDefinition.schema.annotations,
toolDefinition.call,
);
const [serverTransport, clientTransport] =
InMemoryTransport.createLinkedPair();
await server.connect(serverTransport);
client = new Client({ name: "test-client", version: "1.0.0" });
await client.connect(clientTransport);
});
test("schema describes tool", async () => {
const tools = await client.listTools();
expect(tools.tools[0]).toStrictEqual({
name: "conversation_topics",
title: undefined,
_meta: undefined,
annotations: { title: "Conversation Topics" },
description:
"Retrieves Speech and Text Analytics topics detected for a specific conversation. Topics represent business-level intents (e.g. cancellation, billing enquiry) inferred from recognised phrases in the customer-agent interaction.",
inputSchema: {
type: "object",
properties: {
conversationId: {
description:
"A UUID for a conversation. (e.g., 00000000-0000-0000-0000-000000000000)",
format: "uuid",
type: "string",
},
},
required: ["conversationId"],
additionalProperties: false,
$schema: "http://json-schema.org/draft-07/schema#",
},
});
});
test("errors when no conversation ID provided", async () => {
await expect(
client.callTool({
name: toolName,
arguments: {
conversationId: "",
},
}),
).rejects.toSatisfy(
(error: McpError) =>
error.name === "McpError" &&
error.message.includes("conversationId") &&
error.message.includes("Invalid uuid"),
);
});
test("sentiment returned for single conversation", async () => {
const conversationId = randomUUID();
toolDeps.analyticsApi.getAnalyticsConversationDetails.mockResolvedValue({
conversationStart: "2025-05-19T20:00:07.395Z",
conversationEnd: "2025-05-19T21:00:52.686Z",
});
toolDeps.analyticsApi.postAnalyticsTranscriptsAggregatesQuery.mockResolvedValue(
{
results: [
{ group: { topicId: "test-topic-id-1" } },
{ group: { topicId: "test-topic-id-2" } },
],
},
);
toolDeps.speechTextAnalyticsApi.getSpeechandtextanalyticsTopics.mockResolvedValue(
{
entities: [
{
name: "Test Topic 1",
description: "Test Topic 1 Desc",
},
{
name: "Test Topic 2",
description: "Test Topic 2 Desc",
},
],
},
);
const result = await client.callTool({
name: toolName,
arguments: {
conversationId: conversationId,
},
});
expect(result).toStrictEqual({
content: [
{
type: "text",
text: JSON.stringify({
conversationId: conversationId,
detectedTopics: [
{ name: "Test Topic 1", description: "Test Topic 1 Desc" },
{ name: "Test Topic 2", description: "Test Topic 2 Desc" },
],
}),
},
],
});
});
});
