About Simple MCP Server
Simple MCP Server is a Python-based local MCP server example configured for Claude Desktop. The README describes setup and client configuration but does not specify the tools or other capabilities it provides.
Key features
- 01Python virtual environment setup
- 02Dependency installation with pip
- 03Claude Desktop configuration
Use cases
- 01Setting up a local MCP server for Claude Desktop
- 02Following a basic MCP server setup
MCP support
The README shows how to configure the server in Claude Desktop, but does not describe the MCP tools or resources it exposes.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMESimple MCP Server
Setup Environment
- Create virtual environment and activate
python3 -m venv venv
# Ubuntu
source ./venv/bin/activate
# Windows
.\venv\Scripts\activate
- Install dependencies
pip install -r requirements.txt
Claude Desktop Configuration
- Create the config file in claude installation folder (C:\Users\admin\AppData\Roaming\Claude\claude_desktop_config.json)
{
"mcpServers": {
"weather": {
"command": "C:\\my\\lessions\\mcp\\simple-server\\venv\\Scripts\\python.exe",
"args": [
"C:\\my\\lessions\\mcp\\simple-server\\server.py"
]
}
}
}
- Exit Claude and re-launch
- Notice the newly added tools
Reference
-
MCP (Model Context Protocol) Simplified
https://blog.stackademic.com/mcp-model-context-protocol-simplified-976b46f01efd -
Build a Simple Local MCP Server
https://blog.stackademic.com/build-simple-local-mcp-server-5434d19572a4 -
Adding Prompts to MCP Server
https://blog.stackademic.com/adding-prompts-to-mcp-server-64d058c4e758
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.