Commands

Provides a Python MCP server to manage notes with AI summarization via Claude Desktop.

python

0

GitHub Stars

python

Language

7 months ago

First Indexed

3 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "yash-pisat-mcpservertutorial": {
      "command": "uv",
      "args": [
        "run",
        "mcp",
        "install",
        "main.py"
      ]
    }
  }
}

You can run a Python-based MCP server that lets you create, read, update, and summarize sticky notes using an AI agent like Claude via Claude Desktop. This server exposes practical actions you can perform from any MCP client, such as adding notes, listing all notes, fetching the latest one, and asking Claude to summarize your notes.

How to use

You interact with the server through an MCP client. Ask it to add a note, read all notes, fetch the latest note, or prompt Claude to summarize your notes. The server handles storage in a local file and exposes AI-assisted summaries that you can request at any time.

How to install

Prerequisites you need before starting:

• Python 3.8+

• Claude Desktop installed

• uv (recommended for dependency management)

• MCP Python SDK

Step-by-step commands to set up and run the server:

# Windows
irm https://astral.sh/uv/install.ps1 | iex

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

uv init . |sh

uv add mcp-cli

uv run mcp install main.py

Additional content

Claude Desktop integration steps: open Claude Desktop, go to Settings > Developer > Edit Config, and add your MCP server using the generated uv command. Then restart Claude to apply the changes.

Notes and concepts

The server leverages FastMCP concepts and ACtions such as @mcp.tool for executable functions, @mcp.resource for context data (like the latest notes), and @mcp.prompt for reusable prompts used by AI agents.

Available tools

mcp.tool

Executable functions exposed by the MCP server to perform actions like adding, reading, and updating notes.

mcp.resource

Context data providers used by the AI prompts, such as the latest notes.

mcp.prompt

Reusable prompts that guide the AI agent in processing and summarizing notes.