# db-memory

> Use this tool when you need to leverage conversational memory for AI agents, storing and retrieving solved problems and solutions as vectors to inform responses to new, similar requests. It solves the problem of knowledge retention and recall in conversational AI, enabling more accurate and contextually relevant responses. The db-memory tool takes in new requests as input and outputs relevant past solutions, facilitating efficient and effective conversational learning.

Canonical page: https://skillsregistry.net/skills/ak1ena-vector-db-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ak1ena-vector-db-mcp

## Description

A vector-DB MCP server that gives Claude conversational memory by storing solved problems and solutions as vectors and retrieving relevant ones when a new request resembles a past solution.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mqamxst77j)
- **Repository:** <https://github.com/Ak1Ena/vector-db-mcp>

## 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": "ak1ena-vector-db-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ak1ena-vector-db-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ak1ena-vector-db-mcp/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