AI Sticky Notes
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AI Sticky Notesadd a sticky note: don't forget to water the plants"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
๐ AI Sticky Notes - Python MCP Server
A lightweight, client-agnostic Model Context Protocol (MCP) server built in Python using FastMCP. This server exposes persistent note-taking capabilities to AI assistants (such as Claude Desktop, Google Antigravity, Cursor, and any MCP-compliant client).
๐ Key Features
This server implements the three core primitives of the Model Context Protocol:
๐ ๏ธ Tools (Action Execution):
add_note(message: str) -> str: Appends a new sticky note to the local storage file.read_notes() -> str: Reads and returns all saved notes formatted as a single string.
๐ฆ Resources (Context Feeds):
notes://latest: Exposes the most recently saved note dynamically over a custom URI.
๐ฌ Prompts (Reusable LLM Templates):
note_summary_prompt(): Generates a ready-to-use prompt directing the AI to summarize all current sticky notes.
๐ Project Structure
.
โโโ main.py # Primary FastMCP server implementation
โโโ main_final.py # Clean reference implementation
โโโ notes.txt # Persistent note storage (auto-generated)
โโโ pyproject.toml # uv / Python package and dependency configuration
โโโ BITACORA_DE_ERRORES.md # Troubleshooting log & root-cause analyses (Linux & PATH notes)
โโโ MCP_PYTHON_SDK.md # FastMCP quick reference cheatsheet
โโโ README.md # Project documentation (this file)๐ Getting Started
Prerequisites
Python 3.12+
uv (recommended for fast package and environment management)
1. Installation
Clone this repository and sync the dependencies:
git clone https://github.com/<your-username>/<your-repo-name>.git
cd <your-repo-name>
uv sync๐งช Running & Testing
Option A: Interactive MCP Inspector (Recommended)
The MCP Inspector provides a visual web interface to test tools, inspect resources, and execute prompts interactively:
uv run mcp dev main.pyOpen the URL displayed in the terminal (usually http://localhost:5173 or similar) to interact with your server.
Option B: Claude Desktop Integration
Add the server definition to your claude_desktop_config.json:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.jsonLinux:
~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"ai-sticky-notes": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/your/project",
"run",
"main.py"
]
}
}
}๐ก Linux / GUI Environment Tip: If your desktop environment does not inherit your shell's interactive
PATH(causingspawn uv ENOENT), specify the absolute path to youruvbinary (e.g./home/<user>/.local/bin/uvor/home/<user>/miniconda3/bin/uv). See BITACORA_DE_ERRORES.md for details.
Option C: Integration with Standard MCP Clients (Cursor, Antigravity, Custom CLI)
Configure standard stdio transport using:
Command:
uvArgs:
["--directory", "<PROJECT_PATH>", "run", "main.py"]
๐ MCP API Reference
Tools
Name | Parameters | Return Type | Description |
|
|
| Adds a new note line to |
| (none) |
| Returns all recorded notes or |
Resources
URI Pattern | Name / Description | Return Content |
| Get Latest Note | Text content of the last recorded note |
Prompts
Name | Arguments | Description |
| (none) | Returns a prompt asking the AI model to summarize the current notes |
๐ ๏ธ Development & Troubleshooting
For a detailed changelog of debugging steps, Linux platform workarounds, and common setup issues encountered during development, refer to:
๐ BITACORA_DE_ERRORES.md (Log in Spanish)
๐ MCP_PYTHON_SDK.md (SDK Cheatsheet)
๐ License & Credits
Built with Model Context Protocol and FastMCP.
Inspired by the MCP server development tutorial by Tech With Tim.
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