# pyvector

> pyvector — modzer0-pyvector. Use this tool when you need to efficiently manage and query vector data for local large language model (LLM) applications. PyVector solves problems related to vector database management, providing a lightweight implementation with MCP server support and minimal dependencies. It accepts vector data as input and outputs query results, ideal for use cases requiring fast and reliable vector data retrieval in resource-constrained environments.

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

## Description

A lightweight vector database implementation with Model Context Protocol (MCP) server support, designed for local LLM applications. PyVector works with minimal dependencies and provides fallback implementations when optional dependencies are not available.

## Trust

- **Trust score (0–1):** 0.92
- **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/pyvector)

## 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-pyvector"
    }
  }
}
```

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