# AI Sticky Notes MCP Server

> AI Sticky Notes MCP Server — aakash-agrahari-claude-connector-notes-mcp-server. Use this tool when you need to manage and summarize local notes using AI-powered assistance. It solves problems of note organization and information retrieval by allowing users to add, read, and retrieve notes, as well as generate AI-driven summaries through natural language inputs. The tool accepts text-based notes as input and outputs summarized information, making it ideal for users seeking to streamline their note-taking and information review processes.

Canonical page: https://skillsregistry.net/skills/aakash-agrahari-claude-connector-notes-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/aakash-agrahari-claude-connector-notes-mcp-server

## Description

Enables AI assistants to manage local sticky notes, allowing users to add, read, retrieve the latest note, and generate AI summaries through natural language.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/e5bu34i29n)
- **Repository:** <https://github.com/Aakash-Agrahari/claude_connector_notes_mcp_server>

## 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": "aakash-agrahari-claude-connector-notes-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/aakash-agrahari-claude-connector-notes-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/aakash-agrahari-claude-connector-notes-mcp-server/pull`

---
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