# BookmarkMemory

> Use this tool when you need to semantically search and retrieve bookmarked URLs' content using vector embeddings. It solves problems of information overload and difficulty in finding relevant content among bookmarks, providing a powerful search interface with multiple backend support. Ideal for use cases where AI-driven content retrieval and organization are necessary, with outputs tailored for AI assistant integration.

Canonical page: https://skillsregistry.net/skills/deenihl-bookmarkcontext  
JSON: https://api.skillsregistry.net/v1/skills/deenihl-bookmarkcontext

## Description

Enables semantic search and retrieval of bookmarked URLs content using vector embeddings, with support for multiple backends and AI assistant integration.

## 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:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/olfkqpge0z)
- **Repository:** <https://github.com/DeeNihl/BookmarkContext>

## 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": "deenihl-bookmarkcontext"
    }
  }
}
```

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