MCP Servers

Name: MCP Servers
Author: connectwithprakash

@connectwithprakash

リポジトリ

MCP Servers について

Repository for my MCP servers

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

connectwithprakash

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "great-learning-mcp": {
      "command": "/path/to/python/virtualenv",
      "args": [
        "/path/to/mcp-servers/great_learning/great_learning_mcp.py"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP Servers?

MCP Servers is a repository containing a collection of self-contained Model Context Protocol (MCP) implementations that enhance AI assistants with custom capabilities, such as accessing external tools, data sources, and proprietary information. It is designed for developers and users who want to extend AI assistants like Claude, Cursor, or Windsurf with specialized functions.

How to use MCP Servers?

Clone the repository, install dependencies with Poetry (Python 3.12+), and add the desired MCP’s configuration to your assistant’s MCP config file (e.g., ~/.cursor/mcp.json for Cursor). Provide the JSON with the path to a virtualenv and the MCP script’s arguments.

Key features of MCP Servers

Collection of self-contained MCP implementations for specific tasks
Great Learning MCP enables semantic search over course content
Detailed information retrieval for individual courses
Course comparison functionality
Full access to Great Learning documentation

Use cases of MCP Servers

AI assistant accessing up‑to‑date educational course information
Searching and comparing Great Learning programs
Integrating proprietary or private training data into assistant responses

FAQ from MCP Servers

What are the dependencies for using MCP Servers?

Python 3.12+, Poetry for dependency management, and any additional requirements specified in each MCP’s own README.

How do I configure an MCP server for my AI assistant?

Add the configuration to your assistant’s MCP configuration file (e.g., ~/.cursor/mcp.json for Cursor, ~/.claude.json for Claude Code) using the JSON format shown in the README with the correct command and args.