# VecMory

> Use this tool when you need to enhance AI agents with contextual memory, enabling them to learn from past queries, errors, and solutions. VecMory solves problems of knowledge retention and retrieval, providing a typed graph storage with local embedding search for efficient information recall. It accepts query-error-solution chains as input and outputs relevant solutions, ideal for use cases requiring cumulative knowledge and adaptive learning.

Canonical page: https://skillsregistry.net/skills/judas-priest-vecmory  
JSON: https://api.skillsregistry.net/v1/skills/judas-priest-vecmory

## Description

An MCP server that provides AI agents with a contextual memory system, storing query-error-solution chains as a typed graph with local embedding search.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/m9f346idqn)
- **Repository:** <https://github.com/judas-priest/vecmory>

## 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": "judas-priest-vecmory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/judas-priest-vecmory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/judas-priest-vecmory/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