# Rememberizer Vector Store MCP Server

> Use this tool when you need to integrate large language models (LLMs) with a vector store for advanced semantic search and document management capabilities. It solves problems related to information retrieval, document creation, and modification, enabling efficient interaction between LLMs and the Rememberizer Vector Store. This tool accepts LLM queries as input and returns relevant search results or modified documents as output.

Canonical page: https://skillsregistry.net/skills/skydeckai-mcp-rememberizer-vectordb  
JSON: https://api.skillsregistry.net/v1/skills/skydeckai-mcp-rememberizer-vectordb

## Description

Enables LLMs to interact with Rememberizer Vector Store for semantic search, document creation, deletion, and modification.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **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/qwb6nyb3s3)
- **Repository:** <https://github.com/skydeckai/mcp-rememberizer-vectordb>

## 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": "skydeckai-mcp-rememberizer-vectordb"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/skydeckai-mcp-rememberizer-vectordb` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/skydeckai-mcp-rememberizer-vectordb/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