# ChartMogul MCP > ChartMogul MCP gives your AI agent direct access to your SaaS billing data. It lets you analyze Monthly Recurring Revenue, track customer churn rates, and monitor lifetime value without opening a single dashboard. You get real-time financial intelligence on growth patterns, subscription plans, and overall business health directly through conversation. ## Overview - **Category:** data-analytics - **Price:** Free - **Tags:** mrr-tracking, saas-analytics, churn-analysis, ltv-calculation, revenue-intelligence, cohort-analysis ## Description You're tired of jumping between charts and dashboards just to figure out your company's revenue trajectory. This MCP connects your AI agent straight into ChartMogul, giving you immediate control over your SaaS finance data. Instead of exporting CSVs or manually scrubbing filtered views, you talk to your agent about your business performance. It pulls real-time metrics like Monthly Recurring Revenue (MRR) and Annual Run Rate (ARR), lets you understand exactly why customers are leaving by analyzing churn rates, and helps you map out growth patterns over specific time periods. If you use Vinkius, you get this MCP alongside thousands of others, giving your agent a unified view of all your critical business data points—from customer lists to billing plans—all in one chat window. ## Tools ### create_customer_record Adds a new customer record into your system. ### get_summary_metrics Retrieves key, high-level SaaS metrics like MRR and ARR in one call. ### get_api_status Checks the current connection status between your AI client and ChartMogul. ### get_arr_history Analyzes how your Annual Run Rate (ARR) has changed over time for trend spotting. ### get_churn_rates Calculates and analyzes customer retention and churn rates for a given period. ### get_customer_count_history Tracks the total number of users or customers over various time periods to monitor growth. ### get_customer_details Fetches a detailed profile for any specific customer account, including historical data. ### get_customer_ltv Calculates the estimated Lifetime Value (LTV) for individual customers based on their tenure and spending. ### get_mrr_history Analyzes the Monthly Recurring Revenue (MRR) trend, showing how your core revenue has changed monthly. ### list_customers Retrieves a complete list of all active and past SaaS customers in your account. ### list_data_sources Lists all billing providers or data feeds connected to ChartMogul for oversight. ### list_subscription_plans Shows the names, pricing tiers, and details of all billing plans you offer. ## Prompt Examples **Prompt:** ``` Show our MRR and ARR summary for the last 3 months. ``` **Response:** ``` I've retrieved your revenue metrics. Over the last 3 months, your MRR grew by 15%, reaching $54,200. ARR is currently at $650,400. Would you like a breakdown of growth by subscription plan? ``` **Prompt:** ``` What is our current churn rate compared to last month? ``` **Response:** ``` Scanning retention metrics... Your current churn rate is 2.4%, down from 2.8% last month. Customer retention is improving. Shall I list the customers who cancelled recently? ``` **Prompt:** ``` Get the MRR contribution for customer 'john.doe@example.com'. ``` **Response:** ``` Fetching profile... John Doe (ID: uuid_123) contributes $150 to your MRR through a 'Premium Plan'. His LTV is estimated at $4,500 based on his 12-month tenure. Need any other details from his history? ``` ## Capabilities ### Calculate core revenue metrics The agent retrieves real-time Monthly Recurring Revenue (MRR) and Annual Run Rate (ARR) figures for your business. ### Analyze customer retention and loss rates You can check current churn rates and analyze Lifetime Value (LTV) across custom time ranges to assess overall user health. ### Manage and profile the subscriber base The agent lists your entire customer roster and retrieves detailed historical profiles for any given account. ### Track growth trends over time You can query how user counts or specific revenue metrics have changed across days, weeks, months, or quarters. ## Use Cases ### Reviewing Quarter-End Performance A founder needs to summarize Q3 revenue. They ask their agent, 'Show me the MRR history for the last three months.' The MCP uses get_mrr_history and get_summary_metrics to provide an instant, detailed breakdown of growth that they can immediately use in a board meeting. ### Identifying Revenue Leakage A finance manager notices revenue slowing down. They ask the agent about churn rates. The MCP runs get_churn_rates and identifies a specific drop-off point, allowing the team to focus retention efforts immediately. ### Onboarding a New Client A salesperson needs to know how valuable a potential client is. They ask the agent to check customer LTV for that domain. The MCP runs get_customer_ltv, giving them key data points to close the deal faster. ### Auditing Billing Infrastructure A CTO needs to confirm all payment methods are linked correctly. They ask the agent to list connected sources. The MCP runs list_data_sources, confirming Stripe and Braintree data feeds are active. ## Benefits - Stop manually pulling charts. Instead of exporting CSVs or filtering dashboards, you simply ask the agent to 'What was our MRR last quarter?' and get a direct answer. - Track user growth over time with calls like get_customer_count_history. You can see exactly how your user base changed month-over-month without needing specialized BI tools. - Understand customer health by running analyses on churn rates using get_churn_rates, spotting retention dips faster than waiting for a finance report. - Deep dive into individual accounts: Use get_customer_details or get_customer_ltv to instantly know how much a key client contributes and their predicted long-term value. - Map out your entire billing structure. You can list all available plans with list_subscription_plans, ensuring your AI agent knows exactly what pricing models exist. - Get an immediate financial snapshot using get_summary_metrics for MRR and ARR, giving you a high-level overview of business performance in seconds. ## How It Works The bottom line is you talk about finance metrics, and the MCP handles pulling the structured data from ChartMogul for your AI client to read. 1. Subscribe to this MCP and grab your API Key from the ChartMogul settings dashboard. 2. Connect your AI client (Claude, Cursor, etc.) to Vinkius using that key. 3. Ask your agent questions like 'What was our MRR last quarter?' or 'Show me high-value customers'—and get instant data. ## Frequently Asked Questions **Can ChartMogul MCP calculate MRR based on custom date ranges?** Yes, it can analyze your Monthly Recurring Revenue (MRR) for specific periods. You use get_mrr_history to pinpoint exactly how revenue changed over any given time frame. **What is the difference between list_customers and list_users?** list_customers provides a comprehensive roster of your SaaS customers, while other tools like get_customer_details provide granular information about individual accounts. It's for billing oversight. **Does ChartMogul MCP handle user roles or permissions?** No, this MCP focuses exclusively on revenue intelligence and subscription metrics. Tools are limited to financial data retrieval like get_churn_rates and LTV calculations. **How do I check if the connection is working with ChartMogul MCP?** You use the get_api_status tool. This confirms that your AI client has live access to the necessary billing data in ChartMogul.