# Erlvectordb

> Erlvectordb — modzer0-erlvectordb. Use this tool when you need to efficiently manage and query large volumes of vector data with high performance and fault tolerance. Erlvectordb solves problems related to scalable and concurrent vector operations, providing a reliable solution for applications that require fast and accurate data retrieval. It accepts vector data as input and outputs query results, ideal for use cases that demand low-latency and high-throughput vector searches.

Canonical page: https://skillsregistry.net/skills/modzer0-erlvectordb  
JSON: https://api.skillsregistry.net/v1/skills/modzer0-erlvectordb

## Description

A high-performance MCP (Model Context Protocol) vector database implemented in Erlang/OTP, designed to take full advantage of the Actor model and OTP supervision trees for fault-tolerant, concurrent vector operations.

## Trust

- **Trust score (0–1):** 0.96
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** GPL-3.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Modzer0/Erlvectordb)

## 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": "modzer0-erlvectordb"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/modzer0-erlvectordb` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/modzer0-erlvectordb/pull`

---
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