Practera MCP Server

What is Practera MCP Server?

Practera MCP Server is an MCP (Model Context Protocol) server that provides access to Practera’s GraphQL API, enabling AI models to query Practera learning data. It is designed for learning designers (author users) who want to analyze and restructure projects and assessments using LLMs.

How to use Practera MCP Server?

Install dependencies with npm install, then run locally with npm run dev (server at http://localhost:3000/sse). For production, build with npm run build and deploy to AWS Lambda using npm run deploy with required OAuth parameters. Connect from an MCP client (e.g., Claude Desktop) by providing your Practera API key, region, and optionally OAuth configuration.

Key features of Practera MCP Server

• Server-Sent Events (SSE) transport for MCP
• AWS Lambda deployment support
• GraphQL integration with the Practera API
• Region‑specific endpoints (usa, aus, euk, p2‑stage)
• API key authentication (current) and OAuth 2.1 (coming soon)

Use cases of Practera MCP Server

• Analyze project structure to extend or compress it
• Restructure projects for different grade levels or audiences
• Evaluate and improve assessments within a project
• Generate project blueprints, templates, and assessment questions
• Create Common Cartridge versions or import from LMS data files

FAQ from Practera MCP Server

What is the Practera MCP Server and who is it for?

It is an MCP server that lets AI models query Practera learning data. Currently, it is only available to learning designers (author users).

What authentication methods are supported?

The server supports API key authentication (currently) and OAuth 2.1 (forthcoming). When using API key auth, you supply an apikey and region parameter.

What are the prerequisites to use the server?

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

What MCP tools are available?

The server exposes two tools: mcp_practera_get_project to retrieve project details and mcp_practera_get_assessment to retrieve assessment details.