About MCP demo (DeepSeek as Client's LLM)
A small demo pairing a DeepSeek-powered MCP client with a weather server. The README documents setting a DeepSeek API key and launching the client with a server script.
Key features
- 01DeepSeek API key configuration
- 02MCP client and server demo
- 03Weather server script launch
Use cases
- 01Trying a DeepSeek-based MCP demo
- 02Running the weather server with a client
MCP support
The project is described as an MCP client-and-server demo. The documented command runs the client with `weather.py` as its server script.
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 demo (DeepSeek as Client's LLM)
How to run
-
Config
.envfileAdd
.envfile in project root and add DeepSeek api key:# DeepSeek DEEPSEEK_API_KEY= -
Run MCP Client & Server
$ pip install -r requirements.txt $ python client.py weather.py
Reference
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.