# Sticky Notes

> Use this tool when you need to manage personal notes and reminders through AI conversations, solving problems like information overload and disorganization. It allows users to create, read, and summarize notes, providing a simple interface for adding, reading, and accessing notes stored in a plain text file. Ideal for use cases where quick note-taking and retrieval are necessary, such as jotting down ideas or to-do lists within AI interactions.

Canonical page: https://skillsregistry.net/skills/anish-1101-lab-sticky-notes  
JSON: https://api.skillsregistry.net/v1/skills/anish-1101-lab-sticky-notes

## Description

AI Sticky Notes is a simple MCP server implementation that allows users to create, read, and manage notes through AI interactions. Built with Python using the FastMCP framework, it provides tools for adding notes, reading all stored notes, accessing the latest note, and generating summaries of existing notes. The implementation stores notes in a plain text file, making it lightweight and easy to use for personal note-taking tasks directly within AI conversations.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/anish-1101-lab-sticky-notes)
- **Repository:** <https://github.com/anish-1101-lab/mcp-notes-making>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "anish-1101-lab-sticky-notes"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/anish-1101-lab-sticky-notes` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/anish-1101-lab-sticky-notes/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt