About MCP-Server
MCP-Server is a repository containing two MCP server projects: one exposes shell command execution, and the other offers sentiment analysis. It is intended for LLM applications and custom clients that need these tools.
Key features
- 01Terminal tool for shell commands
- 02Sentiment analysis tool
- 03Python MCP SDK implementation
Use cases
- 01Run shell commands from an LLM application
- 02Request sentiment analysis from a custom client
MCP support
The Shellserver branch exposes a terminal tool through MCP. The client-server-sentiment branch exposes a sentiment analysis tool for MCP clients.
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
Projects on MCP server
You can browse the below branches under my MCP-Server repo:
Shellserver
- A simple MCP (Model Context Protocol) server that provides a terminal tool for executing shell commands.
- It's built using the MCP Python SDK and enables LLM applications like Claude to run commands on your system.
- 🔗Branch Link: https://github.com/P-RajaRamesh/MCP-Server/tree/Shellserver
client-server-sentiment
- This project exposes the sentiment analysis tool from mcp_server.py and that tool will be consumed in any client application like claude or any custom client application like mcp_client.py
- 🔗Branch Link: https://github.com/P-RajaRamesh/MCP-Server/tree/client-server-sentiment
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.