Dodo Payments TypeScript MCP Server
It is generated with Stainless.
Installation
Direct invocation
You can run the MCP Server directly via npx:
export DODO_PAYMENTS_API_KEY="My Bearer Token"
export DODO_PAYMENTS_ENVIRONMENT="live_mode"
npx -y dodopayments-mcp@latest
Via MCP Client
There is a partial list of existing clients at modelcontextprotocol.io. If you already
have a client, consult their documentation to install the MCP server.
For clients with a configuration JSON, it might look something like this:
{
"mcpServers": {
"dodopayments_api": {
"command": "npx",
"args": ["-y", "dodopayments-mcp", "--client=claude", "--tools=dynamic"],
"env": {
"DODO_PAYMENTS_API_KEY": "My Bearer Token",
"DODO_PAYMENTS_ENVIRONMENT": "live_mode"
}
}
}
}
Exposing endpoints to your MCP Client
There are two ways to expose endpoints as tools in the MCP server:
- Exposing one tool per endpoint, and filtering as necessary
- Exposing a set of tools to dynamically discover and invoke endpoints from the API
Filtering endpoints and tools
You can run the package on the command line to discover and filter the set of tools that are exposed by the
MCP Server. This can be helpful for large APIs where including all endpoints at once is too much for your AI's
context window.
You can filter by multiple aspects:
--toolincludes a specific tool by name--resourceincludes all tools under a specific resource, and can have wildcards, e.g.my.resource*--operationincludes just read (get/list) or just write operations
Dynamic tools
If you specify --tools=dynamic to the MCP server, instead of exposing one tool per endpoint in the API, it will
expose the following tools:
list_api_endpoints- Discovers available endpoints, with optional filtering by search queryget_api_endpoint_schema- Gets detailed schema information for a specific endpointinvoke_api_endpoint- Executes any endpoint with the appropriate parameters
This allows you to have the full set of API endpoints available to your MCP Client, while not requiring that all
of their schemas be loaded into context at once. Instead, the LLM will automatically use these tools together to
search for, look up, and invoke endpoints dynamically. However, due to the indirect nature of the schemas, it
can struggle to provide the correct properties a bit more than when tools are imported explicitly. Therefore,
you can opt-in to explicit tools, the dynamic tools, or both.
See more information with --help.
All of these command-line options can be repeated, combined together, and have corresponding exclusion versions (e.g. --no-tool).
Use --list to see the list of available tools, or see below.
Specifying the MCP Client
Different clients have varying abilities to handle arbitrary tools and schemas.
You can specify the client you are using with the --client argument, and the MCP server will automatically
serve tools and schemas that are more compatible with that client.
--client=<type>: Set all capabilities based on a known MCP client- Valid values:
openai-agents,claude,claude-code,cursor - Example:
--client=cursor
- Valid values:
Additionally, if you have a client not on the above list, or the client has gotten better
over time, you can manually enable or disable certain capabilities:
--capability=<name>: Specify individual client capabilities- Available capabilities:
top-level-unions: Enable support for top-level unions in tool schemasvalid-json: Enable JSON string parsing for argumentsrefs: Enable support for $ref pointers in schemasunions: Enable support for union types (anyOf) in schemasformats: Enable support for format validations in schemas (e.g. date-time, email)tool-name-length=N: Set maximum tool name length to N characters
- Example:
--capability=top-level-unions --capability=tool-name-length=40 - Example:
--capability=top-level-unions,tool-name-length=40
- Available capabilities:
Examples
- Filter for read operations on cards:
--resource=cards --operation=read
- Exclude specific tools while including others:
--resource=cards --no-tool=create_cards
- Configure for Cursor client with custom max tool name length:
--client=cursor --capability=tool-name-length=40
- Complex filtering with multiple criteria:
--resource=cards,accounts --operation=read --tag=kyc --no-tool=create_cards
Running remotely
Launching the client with --transport=http launches the server as a remote server using Streamable HTTP transport. The --port setting can choose the port it will run on, and the --socket setting allows it to run on a Unix socket.
Authorization can be provided via the Authorization header using the Bearer scheme.
Additionally, authorization can be provided via the following headers:
| Header | Equivalent client option | Security scheme |
|---|---|---|
x-dodo-payments-api-key |
bearerToken |
API_KEY |
A configuration JSON for this server might look like this, assuming the server is hosted at http://localhost:3000:
{
"mcpServers": {
"dodopayments_api": {
"url": "http://localhost:3000",
"headers": {
"Authorization": "Bearer <auth value>"
}
}
}
}
The command-line arguments for filtering tools and specifying clients can also be used as query parameters in the URL.
For example, to exclude specific tools while including others, use the URL:
http://localhost:3000?resource=cards&resource=accounts&no_tool=create_cards
Or, to configure for the Cursor client, with a custom max tool name length, use the URL:
http://localhost:3000?client=cursor&capability=tool-name-length%3D40
Importing the tools and server individually
// Import the server, generated endpoints, or the init function
import { server, endpoints, init } from "dodopayments-mcp/server";
// import a specific tool
import createCheckoutSessions from "dodopayments-mcp/tools/checkout-sessions/create-checkout-sessions";
// initialize the server and all endpoints
init({ server, endpoints });
// manually start server
const transport = new StdioServerTransport();
await server.connect(transport);
// or initialize your own server with specific tools
const myServer = new McpServer(...);
// define your own endpoint
const myCustomEndpoint = {
tool: {
name: 'my_custom_tool',
description: 'My custom tool',
inputSchema: zodToJsonSchema(z.object({ a_property: z.string() })),
},
handler: async (client: client, args: any) => {
return { myResponse: 'Hello world!' };
})
};
// initialize the server with your custom endpoints
init({ server: myServer, endpoints: [createCheckoutSessions, myCustomEndpoint] });
Available Tools
The following tools are available in this MCP server.
Resource checkout_sessions:
create_checkout_sessions(write):
Resource payments:
create_payments(write):retrieve_payments(read):list_payments(read):retrieve_line_items_payments(read):
Resource subscriptions:
create_subscriptions(write):retrieve_subscriptions(read):update_subscriptions(write):list_subscriptions(read):change_plan_subscriptions(write):charge_subscriptions(write):retrieve_usage_history_subscriptions(read): Get detailed usage history for a subscription that includes usage-based billing (metered components).
This endpoint provides insights into customer usage patterns and billing calculations over time.What You'll Get:
- Billing periods: Each item represents a billing cycle with start and end dates
- Meter usage: Detailed breakdown of usage for each meter configured on the subscription
- Usage calculations: Total units consumed, free threshold units, and chargeable units
- Historical tracking: Complete audit trail of usage-based charges
Use Cases:
- Customer support: Investigate billing questions and usage discrepancies
- Usage analytics: Analyze customer consumption patterns over time
- Billing transparency: Provide customers with detailed usage breakdowns
- Revenue optimization: Identify usage trends to optimize pricing strategies
Filtering Options:
- Date range filtering: Get usage history for specific time periods
- Meter-specific filtering: Focus on usage for a particular meter
- Pagination: Navigate through large usage histories efficiently
Important Notes:
- Only returns data for subscriptions with usage-based (metered) components
- Usage history is organized by billing periods (subscription cycles)
- Free threshold units are calculated and displayed separately from chargeable units
- Historical data is preserved even if meter configurations change
Example Query Patterns:
- Get last 3 months:
?start_date=2024-01-01T00:00:00Z&end_date=2024-03-31T23:59:59Z - Filter by meter:
?meter_id=mtr_api_requests - Paginate results:
?page_size=20&page_number=1 - Recent usage:
?start_date=2024-03-01T00:00:00Z(from March 1st to now)
Resource invoices.payments:
retrieve_invoices_payments(read):retrieve_refund_invoices_payments(read):
Resource licenses:
activate_licenses(write):deactivate_licenses(write):validate_licenses(write):
Resource license_keys:
retrieve_license_keys(read):update_license_keys(write):list_license_keys(read):
Resource license_key_instances:
retrieve_license_key_instances(read):update_license_key_instances(write):list_license_key_instances(read):
Resource customers:
create_customers(write):retrieve_customers(read):update_customers(write):list_customers(read):
Resource customers.customer_portal:
create_customers_customer_portal(write):
Resource customers.wallets:
list_customers_wallets(read):
Resource customers.wallets.ledger_entries:
create_wallets_customers_ledger_entries(write):list_wallets_customers_ledger_entries(read):
Resource refunds:
create_refunds(write):retrieve_refunds(read):list_refunds(read):
Resource disputes:
retrieve_disputes(read):list_disputes(read):
Resource payouts:
list_payouts(read):
Resource products:
create_products(write):retrieve_products(read):update_products(write):list_products(read):archive_products(write):unarchive_products(write):update_files_products(write):
Resource products.images:
update_products_images(write):
Resource misc:
list_supported_countries_misc(read):
Resource discounts:
create_discounts(write): POST /discounts
Ifcodeis omitted or empty, a random 16-char uppercase code is generated.retrieve_discounts(read): GET /discounts/{discount_id}update_discounts(write): PATCH /discounts/{discount_id}list_discounts(read): GET /discountsdelete_discounts(write): DELETE /discounts/{discount_id}
Resource addons:
create_addons(write):retrieve_addons(read):update_addons(write):list_addons(read):update_images_addons(write):
Resource brands:
create_brands(write):retrieve_brands(read): Thin handler just callsget_brandand wraps inJson(...)update_brands(write):list_brands(read):update_images_brands(write):
Resource webhooks:
create_webhooks(write): Create a new webhookretrieve_webhooks(read): Get a webhook by idupdate_webhooks(write): Patch a webhook by idlist_webhooks(read): List all webhooksdelete_webhooks(write): Delete a webhook by idretrieve_secret_webhooks(read): Get webhook secret by id
Resource webhooks.headers:
retrieve_webhooks_headers(read): Get a webhook by idupdate_webhooks_headers(write): Patch a webhook by id
Resource usage_events:
retrieve_usage_events(read): Fetch detailed information about a single event using its unique event ID. This endpoint is useful for:- Debugging specific event ingestion issues
- Retrieving event details for customer support
- Validating that events were processed correctly
- Getting the complete metadata for an event
Event ID Format:
The event ID should be the same value that was provided during event ingestion via the
/events/ingestendpoint.
Event IDs are case-sensitive and must match exactly.Response Details:
The response includes all event data including:
- Complete metadata key-value pairs
- Original timestamp (preserved from ingestion)
- Customer and business association
- Event name and processing information
Example Usage:
GET /events/api_call_12345list_usage_events(read): Fetch events from your account with powerful filtering capabilities. This endpoint is ideal for:- Debugging event ingestion issues
- Analyzing customer usage patterns
- Building custom analytics dashboards
- Auditing billing-related events
Filtering Options:
- Customer filtering: Filter by specific customer ID
- Event name filtering: Filter by event type/name
- Meter-based filtering: Use a meter ID to apply the meter's event name and filter criteria automatically
- Time range filtering: Filter events within a specific date range
- Pagination: Navigate through large result sets
Meter Integration:
When using
meter_id, the endpoint automatically applies:- The meter's configured
event_namefilter - The meter's custom filter criteria (if any)
- If you also provide
event_name, it must match the meter's event name
Example Queries:
- Get all events for a customer:
?customer_id=cus_abc123 - Get API request events:
?event_name=api_request - Get events from last 24 hours:
?start=2024-01-14T10:30:00Z&end=2024-01-15T10:30:00Z - Get events with meter filtering:
?meter_id=mtr_xyz789 - Paginate results:
?page_size=50&page_number=2
ingest_usage_events(write): This endpoint allows you to ingest custom events that can be used for:- Usage-based billing and metering
- Analytics and reporting
- Customer behavior tracking
Important Notes:
- Duplicate Prevention:
- Duplicate
event_idvalues within the same request are rejected (entire request fails) - Subsequent requests with existing
event_idvalues are ignored (idempotent behavior)
- Duplicate
- Rate Limiting: Maximum 1000 events per request
- Time Validation: Events with timestamps older than 1 hour or more than 5 minutes in the future will be rejected
- Metadata Limits: Maximum 50 key-value pairs per event, keys max 100 chars, values max 500 chars
Example Usage:
{ "events": [ { "event_id": "api_call_12345", "customer_id": "cus_abc123", "event_name": "api_request", "timestamp": "2024-01-15T10:30:00Z", "metadata": { "endpoint": "/api/v1/users", "method": "GET", "tokens_used": "150" } } ] }
Resource meters:
create_meters(write):retrieve_meters(read):list_meters(read):archive_meters(write):unarchive_meters(write):