Practera MCP Server

Name: Practera MCP Server
Author: intersective

@intersective

代码仓库

关于 Practera MCP Server

MCP server for Practera

基本信息

分类

其他

许可证

MIT license

运行时

node

传输方式

stdio

发布者

intersective

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "practera": {
      "url": "https://your-lambda-url.lambda-url.us-east-1.on.aws/mcp"
    }
  }
}

工具

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概览

What is Practera MCP Server?

An MCP server that provides access to Practera’s GraphQL API, allowing AI models to query Practera learning data. It is intended for learning designers (author users) who want to analyze and restructure projects and assessments.

How to use Practera MCP Server?

Install dependencies with npm install, then start the server in development mode with npm run dev. The server will be available at http://localhost:3000/sse. For deployment, build with npm run build and deploy to AWS Lambda using the Serverless Framework (requires AWS CLI and OAuth configuration). When connecting from an MCP client, provide an API key and region (or OAuth credentials if using OAuth).

Key features of Practera MCP Server

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

Use cases of Practera MCP Server

Analyze and extend/compress a project’s structure.
Restructure a project for different grade levels or audiences.
Evaluate assessments and suggest improvements.
Generate project blueprints, templates, and assessments.
Create Common Cartridge versions or import projects from other LMS data files.

FAQ from Practera MCP Server

What are the prerequisites for running the server?

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

How do I authenticate with the Practera API?

You can use API key authentication by passing the apikey and region parameters in each tool call. OAuth 2.1 is supported but noted as “coming soon” for production use.

Which MCP tools does the server expose?

Currently two tools are available: mcp_practera_get_project (get project details) and mcp_practera_get_assessment (get assessment details).

Where does the data live?

All data is retrieved from Practera’s GraphQL API. The server does not store or cache data locally.

What transport and deployment options are supported?

The server uses SSE transport and can be run locally on port 3000 or deployed to AWS Lambda using the Serverless Framework.

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