CSM Intelligence MCP Server

A Model Context Protocol (MCP) server that exposes simulated Salesforce CRM data as tools callable by Claude Desktop. Built to demonstrate the same architecture used in production at CData Software — where Claude (MCP client) + CData ConnectAI (MCP server) + live Salesforce data drove weekly CSM account prioritization.

Architecture

Claude Desktop (MCP Client)
        │  MCP Protocol over stdio
        ▼
csm-mcp-server/server.py  ←── This repo
        │  Tool calls
        ▼
data/salesforce.json  (Accounts, Opportunities, Cases, Gong Notes)
        │
        ▼
Claude reasons over returned data
        │
        ▼
Prioritized CSM Weekly Worklist

Setup

1. Install dependencies

cd csm-mcp-server
python3 -m pip install -r requirements.txt

2. Configure Claude Desktop

Open your Claude Desktop config file:

open ~/Library/Application\ Support/Claude/claude_desktop_config.json

Add the server config (merge with any existing config):

{
  "mcpServers": {
    "csm-intelligence": {
      "command": "python3",
      "args": ["/Users/mahesh/csm-mcp-server/server.py"],
      "env": {}
    }
  }
}

3. Restart Claude Desktop

Quit and reopen Claude Desktop. You should see a 🔌 icon or tool count increase in the chat interface.

MCP Tools Exposed

Tool	Description
`get_accounts`	Full account portfolio with ARR, health score, CSM, renewal date
`get_opportunities`	Renewals and expansions with stage, probability, close date
`get_cases`	Open support cases by account and severity
`get_gong_notes`	Call summaries, sentiment, and risk flags from Gong
`get_at_risk_accounts`	Pre-filtered risk signals across all accounts

Demo Prompts

Use these in Claude Desktop after connecting the server:

Weekly prioritization:

"Pull all at-risk accounts and give me a prioritized CSM action list for this week. Include ARR at risk, renewal dates, and top 2 actions per account."

Specific account deep-dive:

"Give me a full picture of Stryker Corporation — open cases, recent Gong call sentiment, renewal status, and what our CSM should do this week."

Revenue at risk summary:

"Which accounts renewing in the next 60 days have health scores below 60? Rank by ARR and tell me what's driving the risk for each."

Churn signal scan:

"Scan all Gong notes for negative sentiment flags and cross-reference with open support cases. Which accounts have both? What's the combined ARR at risk?"

CSM workload view:

"Show me all accounts owned by Mathis Corn. What's his highest priority this week and why?"

The Production Story

At CData Software, this exact architecture ran in production:

Claude Desktop as the MCP client — CSMs used natural language prompts
CData ConnectAI as the MCP server — connected to live Salesforce (with Gong data ingested) and Datadog
Weekly output: prioritized account list with risk flags, driving CSM weekly planning
Outcome: GRR improved from 74% to 83% (~$2M ARR protected)

This repo demonstrates the same pattern with simulated data, making the architecture portable and demonstrable without proprietary dependencies.

CSM Intelligence MCP Server