# io.github.NeerajG03/vector-memory

> Use this tool when you need to store and retrieve documents based on their semantic meaning, utilizing natural language to save and recall files. It solves problems related to information retrieval and document management by leveraging a Redis vector store. The tool accepts text-based inputs and returns relevant documents, making it ideal for applications requiring intelligent document recall and search functionality.

Canonical page: https://skillsregistry.net/skills/io-github-neerajg03-vector-memory  
JSON: https://api.skillsregistry.net/v1/skills/io-github-neerajg03-vector-memory

## Description

Semantic document memory using Redis vector store. Save and recall files with natural language.

## Trust

- **Trust score (0–1):** 0.80
- **Verification tier:** unverified

## Facts

- **Version:** 0.1.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-05-20

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.NeerajG03%2Fvector-memory)

## 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": "io-github-neerajg03-vector-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-neerajg03-vector-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-neerajg03-vector-memory/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