# Arda Vector Database MCP Server

> Use this tool when you need to efficiently search and retrieve code snippets across multiple languages using natural language queries. It solves the problem of manual code searching by enabling fast and cached retrieval of relevant code snippets through integration with a vector database. Ideal for use cases where developers require quick access to specific code segments, such as debugging, code reuse, or knowledge sharing.

Canonical page: https://skillsregistry.net/skills/ardaglobal-mcp-ardaglobal-code  
JSON: https://api.skillsregistry.net/v1/skills/ardaglobal-mcp-ardaglobal-code

## Description

Enables semantic code search across multi-language codebases using natural language queries, integrated with Qdrant vector database for fast, cached retrieval.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/w54atmvkj4)
- **Repository:** <https://github.com/ardaglobal/mcp-ardaglobal-code>

## 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": "ardaglobal-mcp-ardaglobal-code"
    }
  }
}
```

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