MCP-Server-and-client-Implementation-on-Linux
LocalAbout MCP-Server-and-client-Implementation-on-Linux
A Linux-oriented example of building an MCP server and client with Python. It shows project setup and running a client against a local server without Claude Desktop.
Key features
- 01Create an MCP server project
- 02Create an MCP client project
- 03Manage environments and dependencies with uv
- 04Run a local server through the client
Use cases
- 01Learn MCP implementation on Linux
- 02Test a client connection to a local server
MCP support
Demonstrates setting up and running an MCP server and client; the client connects to a local server by script path.
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 READMEMCP-Server-and-client-Implementation-on-Linux
MCP Server and client Implementation on Linux (Rather than using Claude Desktop)
MCP Server ::
Create a new directory for our server
uv init mcp_server_explore cd mcp_server_explore
Create virtual environment and activate it
uv venv source .venv/bin/activate
Install dependencies
uv add "mcp[cli]"
Create our server file
touch mcp_server_explore.py
MCP Client ::
Create a new directory for our client
uv init mcp_client_explore cd mcp_client_explore
Create virtual environment and activate it
uv venv source .venv/bin/activate
Install dependencies
uv add mcp python-dotenv anthropic
Create our server file
touch mcp_client_explore.py
RUN ::
uv run mcp_client_explore.py /workspaces/vsc_dev_mcp_explore/mcp_server_explore/mcp_server_explore.py
YouTube Video ::
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.