What is an MCP Server?

An MCP (Model Context Protocol) server acts as a bridge, allowing AI models to access and interact with external data sources and tools. It standardizes how applications provide context to LLMs.

What is the Practera MCP Server?

The Practera MCP Server allows AI models to query Practera’s GraphQL API, providing access to Practera learning data for analysis and manipulation.

What can I do with the Practera MCP Server?

You can use it to analyze Practera projects, generate assessments, restructure content for different audiences, and more.

What are the prerequisites for using the Practera MCP Server?

You need Node.js 18+, npm, an AWS account (for deployment), a Practera API key, and OAuth client credentials (for OAuth authentication).

How do I install the Practera MCP Server?

Clone the repository and run npm install.

How do I deploy the Practera MCP Server to AWS Lambda?

Configure your OAuth parameters and use the Serverless Framework with npm run deploy.

What authentication methods are supported?

API key authentication and OAuth 2.1 (coming soon).

What MCP tools are available?

mcp_practera_get_project and mcp_practera_get_assessment.

How do I configure the MCP client?

You need to provide the API key (if using API key auth), the Practera region, and OAuth configuration (if using OAuth authentication).

Where can I find more information about UBOS?

Visit https://ubos.tech to learn more about the UBOS platform and its AI Agent capabilities.