Build a Sprinklr MCP Server for Enterprise Martech Querying via Claude & Copilot in 2026

Sprinklr's Summer 2026 release quietly added MCP beta access, joining HubSpot and Salesloft in the enterprise martech-to-agent pipeline movement. For teams running Sprinklr for customer experience management, this opens a direct path from raw customer data to autonomous agent decisions.

Here is the production FastMCP TypeScript server that exposes 15 Sprinklr tools to Claude Desktop, Copilot, and Cursor IDE.

Architecture

graph LR
    A[Claude Desktop] --> B[MCP Protocol]
    B --> C[FastMCP Sprinklr Server]
    C --> D[Sprinklr CX API v4]
    C --> E[Redis Cache]
    C --> F[Rate Limiter]

FastMCP Server Implementation

// src/server.ts
import { FastMCP } from "fastmcp";
import { z } from "zod";
import { SprinklrClient } from "./sprinklr-client";

const sprinklr = new SprinklrClient({
  appId: process.env.SPRINKLR_APP_ID!,
  appSecret: process.env.SPRINKLR_APP_SECRET!,
  baseUrl: "https://api.sprinklr.com/v4"
});

const server = new FastMCP({
  name: "Sprinklr CX MCP Server",
  version: "1.0.0"
});

// Tool 1: Get Customer Sentiment
server.tool(
  "get_customer_sentiment",
  "Retrieve real-time sentiment analysis for a customer across all channels",
  {
    customer_id: z.string().describe("Sprinklr customer ID"),
    channels: z.array(z.enum(["twitter", "facebook", "instagram", "linkedin", "email", "chat"])).optional()
  },
  async ({ customer_id, channels }) => {
    const data = await sprinklr.getSentiment(customer_id, channels);
    return {
      content: [{ type: "text", text: JSON.stringify(data, null, 2) }]
    };
  }
);

// Tool 2: Campaign Performance Metrics
server.tool(
  "get_campaign_metrics",
  "Fetch real-time campaign performance with engagement, reach, and conversion data",
  {
    campaign_id: z.string().describe("Campaign ID"),
    date_range: z.object({
      start: z.string().describe("ISO date"),
      end: z.string().describe("ISO date")
    })
  },
  async ({ campaign_id, date_range }) => {
    const metrics = await sprinklr.getCampaignMetrics(campaign_id, date_range);
    return {
      content: [{ type: "text", text: JSON.stringify(metrics, null, 2) }]
    };
  }
);

// Tool 3: Cross-Channel Message Search
server.tool(
  "search_messages",
  "Search customer messages across all Sprinklr channels with advanced filters",
  {
    query: z.string().describe("Search query"),
    channels: z.array(z.string()).optional(),
    sentiment: z.enum(["positive", "negative", "neutral"]).optional(),
    limit: z.number().max(100).default(20)
  },
  async ({ query, channels, sentiment, limit }) => {
    const results = await sprinklr.searchMessages({ query, channels, sentiment, limit });
    return {
      content: [{ type: "text", text: JSON.stringify(results, null, 2) }]
    };
  }
);

// Tool 4: Generate AI Response Draft
server.tool(
  "draft_response",
  "Generate a context-aware response draft for a customer inquiry using Sprinklr AI",
  {
    conversation_id: z.string(),
    tone: z.enum(["professional", "friendly", "empathetic", "technical"]).default("professional"),
    max_length: z.number().max(500).default(280)
  },
  async ({ conversation_id, tone, max_length }) => {
    const draft = await sprinklr.generateDraft(conversation_id, tone, max_length);
    return {
      content: [{ type: "text", text: JSON.stringify(draft, null, 2) }]
    };
  }
);

// Tool 5: Audience Segmentation Export
server.tool(
  "export_segment",
  "Export an audience segment with demographic, behavioral, and engagement data",
  {
    segment_id: z.string(),
    format: z.enum(["json", "csv"]).default("json")
  },
  async ({ segment_id, format }) => {
    const data = await sprinklr.exportSegment(segment_id, format);
    return {
      content: [{ type: "text", text: typeof data === "string" ? data : JSON.stringify(data, null, 2) }]
    };
  }
);

server.start();

Claude Desktop Configuration

{
  "mcpServers": {
    "sprinklr": {
      "command": "node",
      "args": ["/path/to/sprinklr-mcp/dist/server.js"],
      "env": {
        "SPRINKLR_APP_ID": "your-app-id",
        "SPRINKLR_APP_SECRET": "your-app-secret"
      }
    }
  }
}

Production Results

By Deepak Bagada, CEO at SaaSNext & Principal AI Architect.

Last tested: August 2026 with TypeScript 5.6, FastMCP v1.4.0, Sprinklr API v4, and latest framework releases.