mcp-client-and-server
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Python
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2
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README
mcp-client-and-server MCP server
Model Context Protocol Client and Server to chain together between clients and servers
Components
Resources
The server implements a simple note storage system with:
- Custom note:// URI scheme for accessing individual notes
- Each note resource has a name, description and text/plain mimetype
Prompts
The server provides a single prompt:
- summarize-notes: Creates summaries of all stored notes
- Optional "style" argument to control detail level (brief/detailed)
- Generates prompt combining all current notes with style preference
Tools
The server implements one tool:
- add-note: Adds a new note to the server
- Takes "name" and "content" as required string arguments
- Updates server state and notifies clients of resource changes
Configuration
[TODO: Add configuration details specific to your implementation]
Quickstart
Install
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development/Unpublished Servers Configuration
"mcpServers": {
"mcp-client-and-server": {
"command": "uv",
"args": [
"--directory",
"/Users/mlrsmith/Library/Mobile Documents/com~apple~CloudDocs/Family_Shared/AI/mcp/mcp-client-and-server",
"run",
"mcp-client-and-server"
]
}
}
Published Servers Configuration
"mcpServers": {
"mcp-client-and-server": {
"command": "uvx",
"args": [
"mcp-client-and-server"
]
}
}
Development
Building and Publishing
To prepare the package for distribution:
-
Sync dependencies and update lockfile:
uv sync -
Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
uv publish
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token: `--token` or `UV_PUBLISH_TOKEN`
- Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD`
### Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging
experience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector).
You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:
```bash
npx @modelcontextprotocol/inspector uv --directory /Users/mlrsmith/Library/Mobile Documents/com~apple~CloudDocs/Family_Shared/AI/mcp/mcp-client-and-server run mcp-client-and-server
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
Publisher info
More MCP servers built with Python
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.