# Linkedmash

> Use this tool when you need to efficiently manage and organize LinkedIn bookmarks within AI workflows, solving problems of information overload and disorganization. It provides advanced filtering, searching, and pagination capabilities, accepting inputs such as read status, media type, and date ranges, and outputs bookmark counts and details. Ideal for use cases requiring streamlined bookmark management and integration into AI-driven processes.

Canonical page: https://skillsregistry.net/skills/ramyachinnadurai-linkedmash  
JSON: https://api.skillsregistry.net/v1/skills/ramyachinnadurai-linkedmash

## Description

Enable AI assistants to manage LinkedIn bookmarks with advanced filtering, searching, and pagination capabilities. Access bookmark counts and details filtered by read status, media type, author, tags, and date ranges. Seamlessly integrate Linkedmash bookmark management into your AI workflows using this MCP service.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** social-media
- **Updated:** 2026-05-10

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/RamyaChinnadurai/linkedmash)

## 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": "ramyachinnadurai-linkedmash"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ramyachinnadurai-linkedmash` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ramyachinnadurai-linkedmash/pull`

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