# Vector Memory

> Use this tool when you need to retrieve documents based on their semantic meaning, rather than just keywords. It solves problems of information overload and disorganization by enabling context-aware document retrieval across sessions. With natural language queries as input, Vector Memory outputs relevant files, making it ideal for use cases where intuitive document search and recall are crucial.

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

## Description

Provides semantic document memory capabilities using Redis as a vector store backend. Users can save and recall files using natural language queries, enabling context-aware document retrieval across sessions.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/neerajg03-vector-memory)
- **Repository:** <https://github.com/neerajg03/vector-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": "neerajg03-vector-memory"
    }
  }
}
```

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