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.
@connectwithprakash
Basic information
Repository for my MCP servers
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"great-learning-mcp": {
"command": "/path/to/python/virtualenv",
"args": [
"/path/to/mcp-servers/great_learning/great_learning_mcp.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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.
Python 3.12+, Poetry for dependency management, and any additional requirements specified in each MCP’s own README.
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.
The README lists support for Cursor, Windsurf, Claude Desktop, and Claude Code.
Create a new directory for your MCP, implement it with the MCP SDK
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