AI Sticky Notes MCP Server
Enables AI assistants to save and retrieve persistent sticky notes across conversations, with tools, a resource, and a prompt for note management and summarization.
README
AI Sticky Notes — MCP Server
A minimal Model Context Protocol (MCP) server that gives an AI assistant simple persistent "sticky notes" — the ability to save short notes to a local file and read them back later, across conversations.
What it exposes
The server (server.py) is built with fastmcp / mcp and exposes:
Tools
| Tool | Description |
|---|---|
add_note(message: str) |
Appends a new note to the sticky note file. Returns a confirmation string once saved. |
read_notes() |
Reads and returns all saved notes as a single string. Returns "No notes yet." if the file is empty. |
Resources
| Resource | Description |
|---|---|
notes://latest |
Returns just the most recently added note. Returns "No notes yet." if there are none. |
Prompts
| Prompt | Description |
|---|---|
note_summary_prompt() |
Generates a prompt asking the AI to summarize all current notes. Returns a message noting there's nothing to summarize if the notes file is empty. |
Notes are stored in a plain text file, notes.txt, in the same directory as server.py, with each note on its own line. The file is created automatically on first use.
Project structure
MCPSerrver/
├── server.py # The MCP server: tools, resource, and prompt definitions
├── client.py # A standalone test client that exercises the server over stdio
├── notes.txt # Generated at runtime — stores the notes
├── pyproject.toml # Project metadata and dependencies
├── uv.lock # Locked dependency versions
└── .python-version # Pinned Python version for the project
Requirements
- Python 3.13+
- Dependencies (see
pyproject.toml):fastmcp>=2.14.1mcp[cli]>=2.0.0
Setup
Using uv (recommended, uses the committed lockfile):
git clone git@github.com:pallikop/MCPSerrver.git
cd MCPSerrver
uv sync
Or with pip:
pip install fastmcp mcp[cli]
Running the server
The server communicates over stdio, so it's designed to be launched by an MCP-compatible client (like Claude Desktop, Claude Code, or the included test client) rather than run standalone for interactive use:
python server.py
Testing with the included client
client.py is a small standalone script that connects to server.py over stdio and exercises every tool, resource, and prompt the server exposes:
python client.py
It will:
- List all available tools, resources, and prompts
- Call
add_notewith a test message - Call
read_notesto confirm it was saved - Read the
notes://latestresource - Fetch the
note_summary_promptprompt
Connecting to an MCP client
To use this server with an MCP-compatible client (e.g. Claude Desktop), point the client's MCP server config at server.py, for example:
{
"mcpServers": {
"ai-sticky-notes": {
"command": "python",
"args": ["/path/to/MCPSerrver/server.py"]
}
}
}
Notes on the current implementation
- Notes are stored unencrypted in a local plain-text file (
notes.txt) — there's no authentication or multi-user separation. add_notealways appends; there's currently no way to delete or edit an individual note through the exposed tools.- The notes file path is resolved relative to
server.py's own location, so it will always read/write in the same directory regardless of where the server is launched from.
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