# vector-mcp

> Use this tool when you need to integrate Retrieval-Augmented Generation (RAG) capabilities into AI agents, supporting multiple vector database technologies for efficient collection management and search operations. It solves problems related to scalable and flexible knowledge retrieval, enabling AI agents to access and manage large datasets. The tool accepts input via the MCP Server interface, outputting relevant search results and managed collections.

Canonical page: https://skillsregistry.net/skills/techexpert0119-vector-mcp  
JSON: https://api.skillsregistry.net/v1/skills/techexpert0119-vector-mcp

## Description

Integrates RAG into AI agents via MCP Server, supporting multiple vector database technologies for collection management and search operations.

## Trust

- **Trust score (0–1):** 0.35
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/n757rwihkm)
- **Repository:** <https://github.com/craftingcodegig/vector-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": "techexpert0119-vector-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/techexpert0119-vector-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/techexpert0119-vector-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