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Learning Model Context Protocol

by yarnabrinaversion 0.3.0i★ –iRuns on your computer
Registry nameio.github.yarnabrina/mcp-learning

Install

Overview

Description from the maker (original English)

Basic arithmetic tools with natural-language expression parsing and evaluation.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: DEBUG, RUNTIME_ENVIRONMENT, LOG_LEVEL, LOG_FILE, JSON_RESPONSE, STATELESS_HTTP

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "learning": {
      "command": "uvx",
      "args": [
        "mcp-learning",
        "--host",
        "127.0.0.1",
        "--port",
        "8000",
        "--streamable_http_path",
        "/mcp"
      ],
      "env": {
        "DEBUG": "your-value",
        "RUNTIME_ENVIRONMENT": "your-value",
        "LOG_LEVEL": "your-value",
        "LOG_FILE": "your-value",
        "JSON_RESPONSE": "your-value",
        "STATELESS_HTTP": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add learning --env DEBUG=your-value --env RUNTIME_ENVIRONMENT=your-value --env LOG_LEVEL=your-value --env LOG_FILE=your-value --env JSON_RESPONSE=your-value --env STATELESS_HTTP=your-value -- uvx mcp-learning --host 127.0.0.1 --port 8000 --streamable_http_path /mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "learning": {
      "command": "uvx",
      "args": [
        "mcp-learning",
        "--host",
        "127.0.0.1",
        "--port",
        "8000",
        "--streamable_http_path",
        "/mcp"
      ],
      "env": {
        "DEBUG": "your-value",
        "RUNTIME_ENVIRONMENT": "your-value",
        "LOG_LEVEL": "your-value",
        "LOG_FILE": "your-value",
        "JSON_RESPONSE": "your-value",
        "STATELESS_HTTP": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "learning": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-learning",
        "--host",
        "127.0.0.1",
        "--port",
        "8000",
        "--streamable_http_path",
        "/mcp"
      ],
      "env": {
        "DEBUG": "your-value",
        "RUNTIME_ENVIRONMENT": "your-value",
        "LOG_LEVEL": "your-value",
        "LOG_FILE": "your-value",
        "JSON_RESPONSE": "your-value",
        "STATELESS_HTTP": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • DEBUG env
    Enable additional debug logging output.
  • RUNTIME_ENVIRONMENT env
    Logging/runtime environment.
  • LOG_LEVEL env
    Log level for server output; the server defaults to INFO.
  • LOG_FILE env
    Optional path for a server log file.
  • JSON_RESPONSE env
    Return JSON payloads for HTTP responses instead of newline-delimited JSON.
  • STATELESS_HTTP env
    Disable HTTP keep-alive to serve each request independently.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account yarnabrina, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32655 servers in this category
  • Published to the registry more recently than 65% of the other 32655 servers in this category
  • Basic checks equal to or better than 100% of the other 32655 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Learning Model Context Protocol safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.3.0) reached the registry 20 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, SuperCollider

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Learning Model Context Protocol

This project explores the features and usage of Model Context Protocol (MCP) servers and clients, providing a hands-on learning environment for experimenting with MCP-based tools and workflows.

Documentation

  • Installation Guide — How to set up your environment and install dependencies.
  • Examples & Usage — Step-by-step usage and sample sessions.
  • MCP Server Configuration
  • MCP Client Configuration

Contributing

Please see CONTRIBUTING.md for development and contribution guidelines.

Links

License

This project is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0-or-later).

Copyright (C) 2025-2026 Anirban Ray

See the LICENSE file for details.

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