# Redis Cloud

> Use this tool when you need to integrate large language models (LLMs) with Redis Cloud databases, enabling AI applications to retrieve and utilize relevant context for improved interactions. It solves problems of data accessibility and context provision for LLMs, allowing for more informed and accurate responses. By providing a Model Context Protocol (MCP) server implementation, Redis Cloud facilitates seamless data exchange between LLMs and Redis databases.

Canonical page: https://skillsregistry.net/skills/redis-cloud  
JSON: https://api.skillsregistry.net/v1/skills/redis-cloud

## Description

A Model Context Protocol (MCP) server implementation for Redis Cloud, enabling AI applications to retrieve and use data from Redis Cloud databases as context for LLM interactions.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/redis-cloud)
- **Repository:** <https://github.com/redis/mcp-redis-cloud>

## 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": "redis-cloud"
    }
  }
}
```

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