Cademí MCP

Cademí MCP is a remote Model Context Protocol server that lets AI assistants work with your Cademí account. You connect it once, authorize it by signing in to Cademí, and the assistant can answer questions and make changes on the Cademí API v3 with the permissions of the administrator who authorized it.

The server address is:

https://mcp.cademi.dev/mcp

It uses the Streamable HTTP transport and OAuth. You never copy an API key: the connection is authorized on Cademí itself, is bound to one account, and acts as the administrator who approved it.

What it can do

Composite tools for common questions. Five tools answer a whole support question in one call, such as why a student cannot access a course or what the full structure of a course is. They accept students by e-mail, name, or public ID and products by name or public ID. See Composite tools.
One tool per API operation. 391 tools cover the operations of API release 3.4.7, from users_list to products_update. Each one has the permission, input, and output of the operation it calls. See Tools per operation.
Resources. The Cademí vocabulary, the tool catalog, and the account the connection works on, as context the assistant can read. See Resources.
Prompts. Ready-made investigations: an access problem, a student's experience, and the structure of a course. See Prompts.

Tools that change data are annotated, so clients that support approval prompts ask you before they run them.

Quickstart

Connect. Add https://mcp.cademi.dev/mcp as a remote MCP server in your client. In Claude, add it as a custom connector; in Claude Code, run claude mcp add. See Connect a client.
Authorize. The client opens the Cademí authorization page. Choose your account, sign in as an administrator, and approve the connection. See Authorization and permissions.
Ask. Ask about your account in plain language. The assistant chooses the tools, and asks for your approval before a tool changes data, when the client supports it.

Example questions

"Why can't [email protected] access the Marketing course?"
"What is João Silva enrolled in, and which products can he not access?"
"Show me the full structure of the Marketing course. Which lessons are still drafts?"
"How is the Marketing course sold, and which access schedules does it have?"
"Which account am I connected to, and how many API requests did it make in the last 24 hours?"
"Rename the course Marketing 101 to Marketing Essentials."

The first five are read-only. The last one changes data, so the assistant asks for your approval first when the client supports it.

MCP, CLI, or API

Use	When
Cademí MCP	You want an AI assistant to investigate and act on your account in a conversation, and approve each change in your client.
Cademí CLI	You work in a terminal or in scripts and CI, forward events to a local application, or apply declarative configuration.
Cademí API v3	You build your own integration: your code calls the API directly and receives webhooks.

All three use the same API v3, which checks the permissions of every call. The complete list of operations is in the API reference.

Report a problem

Bugs in the MCP server and feature requests: open an issue at github.com/minhacademi/developers. Include the tool name, the error code, and the request_id when the error has one (Errors and limits).
Questions about using the server: Discussions.
Security vulnerabilities: report them privately at github.com/minhacademi/developers/security, never in an issue.
Questions about your account, plan, or data: contact Cademí support.

Issues and discussions are public. Never paste an API key, a token, a conversation with personal data, or data about your users.