AI Sticky Notes
Enables AI assistants to persistently add, read, and summarize sticky notes through MCP-compliant tools, resources, and prompts.
README
📝 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).
🌟 Key Features
This server implements the three core primitives of the Model Context Protocol:
- 🛠️ 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.
- 📦 Resources (Context Feeds):
notes://latest: Exposes the most recently saved note dynamically over a custom URI.
- 💬 Prompts (Reusable LLM Templates):
note_summary_prompt(): Generates a ready-to-use prompt directing the AI to summarize all current sticky notes.
📂 Project Structure
.
├── main.py # Primary FastMCP server implementation
├── main_final.py # Clean reference implementation
├── notes.txt # Persistent note storage (auto-generated)
├── pyproject.toml # uv / Python package and dependency configuration
├── BITACORA_DE_ERRORES.md # Troubleshooting log & root-cause analyses (Linux & PATH notes)
├── MCP_PYTHON_SDK.md # FastMCP quick reference cheatsheet
└── README.md # Project documentation (this file)
🚀 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 sync
🧪 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.py
Open 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.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"ai-sticky-notes": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/your/project",
"run",
"main.py"
]
}
}
}
💡 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:
uv - Args:
["--directory", "<PROJECT_PATH>", "run", "main.py"]
📖 MCP API Reference
Tools
| Name | Parameters | Return Type | Description |
|---|---|---|---|
add_note |
message: str |
str |
Adds a new note line to notes.txt |
read_notes |
(none) | str |
Returns all recorded notes or "No notes yet" |
Resources
| URI Pattern | Name / Description | Return Content |
|---|---|---|
notes://latest |
Get Latest Note | Text content of the last recorded note |
Prompts
| Name | Arguments | Description |
|---|---|---|
note_summary_prompt |
(none) | Returns a prompt asking the AI model to summarize the current notes |
🛠️ Development & Troubleshooting
For a detailed changelog of debugging steps, Linux platform workarounds, and common setup issues encountered during development, refer to:
- 📓 BITACORA_DE_ERRORES.md (Log in Spanish)
- 📘 MCP_PYTHON_SDK.md (SDK Cheatsheet)
📄 License & Credits
- Built with Model Context Protocol and FastMCP.
- Inspired by the MCP server development tutorial by Tech With Tim.
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