How to Use the Didacte MCP in Claude

Q: How do I configure Didacte to work with Claude Desktop?

Add the configuration block to your local claudedesktopconfig.json file. Provide your Workleap API token and subdomain under the mcpServers key, adding the MCP Server configuration, then restart the application to load the tools.

Q: Can Claude Desktop search for specific Didacte courses using keywords?

Yes. Your agent uses the searchcoursesbytitle tool to scan your entire catalog for specific keywords. It returns matching course titles and IDs directly inside your chat window.

Q: How does Claude Desktop handle large enrollment lists from Didacte?

The listcourseenrollments tool retrieves the user list in chunks. Claude Desktop processes these records sequentially to avoid hitting rate limits on your Workleap account.

Q: Can I check my organization's usage limits?

Yes. The getaccountmetadata tool retrieves your current usage metrics and account limits. Your agent reads this data to prevent over-allocation of resources.

Query Didacte learning metrics and update course enrollments right inside your Claude Desktop chat.

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Connect Didacte MCP to Claude Desktop

Create your Vinkius account to connect Didacte to Claude Desktop and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Didacte with Claude Desktop

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Audit Course Curriculums Instantly

The `list_course_curriculum` tool pulls the exact lesson structure of any course into Claude Desktop. Your agent reads the module hierarchy, checks lesson counts, and finds gaps in your training material without making you click around. No more clicking through the Workleap dashboard just to verify syllabus details. Combined with `get_course_details`, Claude Desktop displays settings and requirements right alongside your active curriculum. This setup lets you audit content quality or prep course updates without leaving your local chat. You get raw course data mapped directly to your workspace.

Monitor Active Learner Progress in Claude Desktop

The `list_active_learning_progress` tool identifies which users are moving through their assigned training. Your agent pulls these live updates to spot learners who are stuck or lagging behind. It processes the raw progress metrics and outputs clean, readable summaries directly in your chat. This MCP Server integration lets you cross-reference progress with `get_user_learning_profile` to get a complete picture of individual histories. You see exact lesson completions and overall scores without loading a heavy browser page.

Manage Organization Users and Access

The `list_organization_users` tool exposes your entire student directory to Claude Desktop. Your agent searches through registered accounts, matches profiles, and confirms who has access to your training materials. Use `list_user_enrollments` alongside this directory to verify which courses a specific student is taking. This MCP setup replaces manual profile lookups and speeds up user administration tasks.

Setup guide

Set up Didacte MCP in Claude Web or Desktop

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.
3

Start a conversation

Open a new chat. The Didacte MCP tools are available immediately — no restart needed.

Endpoint URL

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

No configuration file needed — paste the URL directly in the Claude web interface.

Available on Free (1 connector), Pro, Max, Team, and Enterprise plans.

Prerequisites

Claude Desktop installed (macOS or Windows)
Active Vinkius subscription with a valid endpoint token

1

Open Claude Desktop Settings

Click the menu icon at the top-left corner, go to Settings → Developer → Edit Config. This opens claude_desktop_config.json in your default text editor.
2

Paste the Didacte MCP configuration

Copy the JSON snippet on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Desktop

Close and reopen the application. Claude needs a full restart to load new MCPs — refreshing a conversation is not enough.
4

Verify the connection

Open a new conversation. Click the 🔌 icon at the bottom of the message input. You should see tools listed under didacte-mcp.

json

{
  "mcpServers": {
    "didacte-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Didacte. 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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Common questions about Didacte MCP in Claude Desktop

Add the configuration block to your local `claude_desktop_config.json` file. Provide your Workleap API token and subdomain under the mcpServers key, adding the MCP Server configuration, then restart the application to load the tools.

Yes. Your agent uses the `search_courses_by_title` tool to scan your entire catalog for specific keywords. It returns matching course titles and IDs directly inside your chat window.

The `list_course_enrollments` tool retrieves the user list in chunks. Claude Desktop processes these records sequentially to avoid hitting rate limits on your Workleap account.

Yes. The `get_account_metadata` tool retrieves your current usage metrics and account limits. Your agent reads this data to prevent over-allocation of resources.

Yes. Your learner profiles and enrollment records stay local to your machine. The MCP Server runs in a sandboxed V8 isolate on Vinkius, meaning your API tokens and user data are never stored or logged on external servers.

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