LearningTo MCP Server

Interview prep for AI agents. learningto-mcp exposes the LearningTo.co curriculum, graded challenges and AI feedback tools to any MCP client, so a candidate can practice inside Claude Code, Claude Desktop, Cursor or their own agent instead of switching to a browser.

• Works with Claude Code, Claude Desktop, Cursor, and any MCP-compatible host.

• No install step to try it: npx -y learningto-mcp

• Offline core: curriculum, challenges and the learning path are bundled.

• Optional AI tools: code analysis, hints, explanations, readiness and problem generation call learningto.co and need a free account token.

• Site: https://learningto.co

• Interactive MCP explainer: https://learningto.co/mcp

Quick start

npx -y learningto-mcp

Claude Code

claude mcp add learningto -- npx -y learningto-mcp

For the AI feedback tools, add the session token to the environment:

claude mcp add learningto \\
  --env ALGOVAULT_SESSION_TOKEN=your-session-token \\
  -- npx -y learningto-mcp

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "learningto": {
      "command": "npx",
      "args": ["-y", "learningto-mcp"],
      "env": {
        "ALGOVAULT_SESSION_TOKEN": "your-session-token"
      }
    }
  }
}

Cursor

Add the same server block to Cursor's MCP configuration (.cursor/mcp.json or the global MCP settings), then restart Cursor.

Related MCP server: algofox

Environment variables

Without a token, the five curriculum tools work offline and the AI tools return a readable message explaining what is missing. They do not fail the whole call.

Tools

Example prompts

• "Use learningto to build me a two-week plan for AI engineer interviews, starting from RAG."

• "Quiz me on RAG retrieval with learningto, one question at a time, and grade each answer."

• "Pull the two-sum challenge, let me solve it, then use learningto to review my code and give one hint."

• "Which topics should I study after agents-behavior, and why?"

How it is built

The server is a stdio MCP server written in TypeScript with the official @modelcontextprotocol/sdk. The curriculum and learning-path graph are bundled at build time. The AI tools call the deployed LearningTo API and never receive your account password.

This repository mirrors the published package. The source lives in the private LearningTo app repo; the compiled server in dist/ is what npm installs.

Development

npm install
npm run build
npm start

License

MIT. See LICENSE.