# wredis-mcp

> wredis-mcp — wisrovi-wredis-mcp. Use this tool when you need to design and deploy scalable Redis-backed services with expert patterns and architecture scaffolding. It solves problems of service deployment and management by providing a unified CLI for AI agents to create and manage WRedis/Redis services. The wredis-mcp server takes in service design inputs and outputs deployed services with optimized architecture.

Canonical page: https://skillsregistry.net/skills/wisrovi-wredis-mcp  
JSON: https://api.skillsregistry.net/v1/skills/wisrovi-wredis-mcp

## Description

MCP server enabling AI agents to design and deploy WRedis/Redis-backed services using expert patterns, architecture scaffolding, and a unified CLI.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ycxs6pj3js)
- **Repository:** <https://github.com/wisrovi/wredis_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": "wisrovi-wredis-mcp"
    }
  }
}
```

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