ChartMogul MCP. Analyze MRR, Churn, and LTV in natural conversation.
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…and any MCP-compatible client
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ChartMogul MCP Server tracks SaaS revenue and customer metrics. Use it to pull real-time data on MRR, ARR, and churn rates.
Your AI agent handles complex financial queries—like 'What was our LTV last quarter?'—by calling tools like `get_mrr_history` and `get_churn_rates` directly.
It gives you full visibility into subscription health without manual report building.
What your AI agents can do
Create customer record
Adds a new customer record to the system.
Get api status
Checks the connection status between your AI client and ChartMogul.
Get arr history
Retrieves Annual Run Rate (ARR) data over a specified historical period.
The agent pulls real-time Monthly Recurring Revenue (MRR), Annual Run Rate (ARR), and other key SaaS performance indicators.
The agent analyzes historical and current customer churn rates and calculates the Lifetime Value (LTV) for the subscriber base.
The agent lists all current customers or retrieves the detailed profile and MRR contribution for a specific user.
The agent pulls historical data points, like customer counts or MRR, over custom time ranges (e.g., last quarter, last 3 months).
The agent checks your connected payment sources (Stripe, Braintree) and lists all active subscription plans.
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ChartMogul MCP Server: 12 Tools for SaaS Metrics
These tools let your agent interact with every aspect of your SaaS billing data, from listing customers to calculating historical revenue trends.
019dd0cbcreate customer record
Adds a new customer record to the system.
019dd0cbget api status
Checks the connection status between your AI client and ChartMogul.
019dd0cbget arr history
Retrieves Annual Run Rate (ARR) data over a specified historical period.
019dd0cbget churn rates
Analyzes and retrieves customer churn rates to assess retention health.
019dd0cbget customer count history
Monitors and retrieves the total number of active users over time.
019dd0cbget customer details
Fetches the full profile and specific metrics for a single customer.
019dd0cbget customer ltv
Calculates the estimated Lifetime Value (LTV) for a specified customer.
019dd0cbget mrr history
Analyzes and retrieves Monthly Recurring Revenue (MRR) data over a historical period.
019dd0cbget summary metrics
Gets a snapshot of all key SaaS metrics, including MRR and ARPA.
019dd0cblist customers
Retrieves a list of all current SaaS customers in the system.
019dd0cblist data sources
Lists all payment gateways and data sources connected to ChartMogul.
019dd0cblist subscription plans
Retrieves a list of all active billing plans used by the company.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with ChartMogul, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
ChartMogul MCP Server lets your AI agent track SaaS revenue and customer metrics. You'll pull real-time data on MRR, ARR, and churn rates. Your agent handles complex financial queries—like 'What was our LTV last quarter?'—by calling tools such as get_mrr_history and get_churn_rates directly. You get full visibility into your subscription health without building manual reports.
Calculating Revenue Metrics
Your agent pulls real-time Monthly Recurring Revenue (MRR), Annual Run Rate (ARR), and Average Revenue Per Account (ARPA). You can use get_summary_metrics to get a snapshot of all key SaaS indicators. You'll find get_mrr_history analyzes and gets MRR data over a specific time period, and get_arr_history retrieves ARR data over a historical range.
Determining Customer Health
To check retention, your agent analyzes and gets customer churn rates using get_churn_rates. It also calculates the estimated Lifetime Value (LTV) for any customer using get_customer_ltv. You can monitor growth by tracking the total number of active users over time with get_customer_count_history.
Reviewing Subscriber Lists
Your agent can list every current SaaS customer in the system using list_customers. You can also fetch the full profile and specific metrics for a single user with get_customer_details.
Tracking Historical Growth
You can pull historical data points, like customer counts or MRR, over custom time ranges. get_mrr_history tracks MRR over time, and get_customer_count_history monitors the total number of active users over time.
Verifying Billing Infrastructure
Your agent checks your connected payment sources (like Stripe and Braintree) by listing all data sources with list_data_sources. It also pulls a list of all active billing plans used by your company with list_subscription_plans. You can also see which plans are available by calling list_customers to get a list of current SaaS customers.
System Status and Setup
Your agent verifies the connection status between your AI client and ChartMogul using get_api_status. You can also add new customer records to the system with create_customer_record.
How ChartMogul MCP Works
- 1 Subscribe to the ChartMogul MCP Server and retrieve your API Key from your ChartMogul dashboard.
- 2 Ask your AI client a natural language question (e.g., 'What was our MRR growth last quarter?').
- 3 The agent calls the appropriate tool (e.g.,
get_mrr_history), processes the data, and provides a conversational answer.
The bottom line is, you talk to your agent like a finance analyst, and it pulls the necessary SaaS data from ChartMogul to answer.
Who Is ChartMogul MCP For?
Founders, CEOs, and Product Managers who need instant visibility into subscription health. If you're tired of spending hours exporting CSVs and stitching together charts just to see if your growth is accelerating, this is for you. It lets you run deep financial analysis without leaving your chat window.
Gets instant, high-level summaries on ARR and churn rates using simple language commands.
Monitors ARR trends, tracks customer LTV, and verifies billing data across different plans without needing to open a BI tool.
Automates the retrieval of structured SaaS metrics (MRR, customer counts) for internal reports using simple AI queries.
What Changes When You Connect
- See MRR and ARR summaries instantly. Instead of manually pulling reports, ask the agent to run
get_summary_metricsto get key revenue figures right away. - Track customer losses without leaving your chat. Use
get_churn_ratesto compare current churn against previous months, giving you immediate retention status. - Understand customer value at a glance. The
get_customer_ltvtool calculates a specific user's Lifetime Value, helping you prioritize retention efforts. - See historical growth patterns. Running
get_mrr_historyallows you to visualize MRR changes over weeks or quarters, spotting trends that static dashboards hide. - Audit your billing setup. The
list_data_sourcestool lets you confirm which payment systems (Stripe, Braintree) are connected, ensuring high-fidelity billing oversight.
Real-World Use Cases
Q3 Review: Checking overall revenue growth
The CEO needs to know if the last quarter hit projections. They ask their agent: 'Show our MRR and ARR for the last 3 months.' The agent calls get_mrr_history and get_summary_metrics and replies with the growth percentage and total figures, ending the meeting on solid data.
Onboarding a new client and checking their value
A Sales Manager wants to know the value of a new enterprise client, 'AlphaCorp'. They ask the agent to run get_customer_details and get_customer_ltv. The agent pulls the full profile and estimates the LTV, giving the Sales team immediate context for the follow-up call.
Investigating a sudden dip in user growth
The Product Manager notices user numbers dropped last week. They ask the agent to run get_customer_count_history. The agent returns a historical graph/data point, allowing the PM to pinpoint the exact date the drop started and investigate the cause.
Compliance Check: Verifying billing sources
A Finance Auditor needs to confirm all payment channels are correctly linked. They ask the agent to run list_data_sources. The agent returns a list of connected sources (Stripe, Braintree, etc.), confirming the system's billing integrity.
The Tradeoffs
Manual CSV Exports
Exporting a list of 500 customers to a spreadsheet, then manually writing formulas to calculate LTV or MRR contribution.
→
Instead, ask your agent to run list_customers and then chain calls to get_customer_ltv for the necessary subset, getting the data structured and ready for immediate analysis.
Stale Dashboard Data
Relying on a dashboard that hasn't updated since yesterday to determine current churn rates, leading to inaccurate operational decisions.
→
Run get_churn_rates directly through your agent. This pulls the most current data, giving you real-time operational insight into customer retention.
Over-engineering Reports
Building a custom BI dashboard that requires multiple data joins and complex scheduled ETL jobs just to see a simple historical MRR trend.
→
Use get_mrr_history to query the trend directly via natural language. This is faster and simpler than building a complex data pipeline just for a trend line.
When It Fits, When It Doesn't
Use this server if your primary need is running ad-hoc financial and operational reports on SaaS metrics. You need to answer questions like, 'How did our LTV change when we added Plan X?' or 'What was our MRR last Tuesday?' If your needs are purely internal (e.g., tracking employee PTO or managing inventory), this server won't help. For those, you need a dedicated HR or ERP system. Also, if you only need to store data, use a general database client; this server is for reading and analyzing existing billing data.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ChartMogul. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Stop digging through dozens of tabs to find one metric.
Think about how you usually check your revenue. You open the BI tool, navigate to the 'Subscription Metrics' tab. Then you filter by date range, maybe click through to the 'Cohort' view, and finally, you export the numbers. It's a lot of clicks, and it takes half an hour just to get the raw data.
With this MCP server, you just ask your agent, 'What was our MRR last quarter?' It handles the dashboard navigation and data pulling behind the scenes. You get the number instantly, ready to discuss.
ChartMogul MCP Server: Analyze Customer Health Data
You no longer have to copy-paste customer IDs and then manually check the LTV for each one. You simply ask your agent to run `get_customer_ltv` for a list of IDs, and it compiles the data into a clear response. The manual lookup process is gone.
Your agent turns complicated, siloed billing data into a direct conversation. You get the answer you need, right where you're working, without ever leaving your chat client.
Common Questions About ChartMogul MCP
How do I check my MRR history using the `get_mrr_history` tool? +
The agent needs a time frame. You ask, 'Show me the MRR for the last 6 months.' The agent executes get_mrr_history and returns the trend data. You can then ask follow-up questions about the spikes or dips.
Can I find out a specific customer's LTV using `get_customer_ltv`? +
Yes. You must provide the customer identifier. Prompt the agent: 'What is the LTV for john.doe@example.com?' The agent uses get_customer_ltv to calculate and report the value.
How do I see all the billing plans available? +
Use the list_subscription_plans tool. Just ask the agent to list them, and it gives you the names and details of every plan you've set up.
What is the best way to track customer growth over time? +
Use get_customer_count_history. You need to specify the period (e.g., 'last 12 months'). The agent runs the tool and gives you the historical count, showing growth or decline.
How do I analyze customer retention trends using the `get_churn_rates` tool? +
The get_churn_rates tool analyzes retention by allowing you to specify custom time intervals. You can compare current rates to previous periods to track improvements or declines in customer retention.
What information can I retrieve using the `get_customer_details` tool? +
This tool retrieves a full customer profile, including detailed historical data and their current MRR contribution. It gives you a comprehensive view of an individual subscriber's journey.
Can I see which data sources are connected using `list_data_sources`? +
Yes, the list_data_sources tool shows every source connected to ChartMogul. This helps you confirm that all billing data (like Stripe or Braintree) is feeding into your agent.
How do I automate adding new subscribers using the `create_customer_record` tool? +
Use create_customer_record to programmatically add a new customer record. You just need to provide the necessary details, and your AI agent handles the creation of the record instantly.
How do I find my ChartMogul API Key? +
Log in to your account, navigate to Settings > API, and copy your unique secret key.
Are the MRR and ARR metrics real-time? +
Yes! The metrics tools retrieve the most current calculations based on the data synced into your ChartMogul account.
Can I filter metrics by specific date ranges? +
Absolutely. Use the get_summary_metrics tool and provide start-date and end-date parameters to analyze specific growth periods.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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