# Redis

> Use this tool when you need to integrate caching and key-value storage into your application, solving problems such as slow data retrieval and complex database setups. It provides a standardized interface for interacting with Redis servers and AWS MemoryDB, accepting inputs such as cache keys and values, and outputting stored data. Ideal for use cases requiring fast, in-memory data storage and retrieval, such as caching, session management, and real-time analytics.

Canonical page: https://skillsregistry.net/skills/prajwalnayak7-redis  
JSON: https://api.skillsregistry.net/v1/skills/prajwalnayak7-redis

## Description

This MCP server, developed by Prajwal S Nayak, provides a Redis integration for caching and key-value storage use cases. Built with Python and leveraging the Model Context Protocol, it offers tools to interact with Redis servers and AWS MemoryDB. The implementation focuses on providing a standardized interface for Redis operations within the MCP ecosystem, supporting both local and cloud-based Redis deployments. It's particularly useful for applications requiring fast, in-memory data storage and retrieval, enabling use cases such as caching frequently accessed data, managing session information, and implementing real-time analytics without complex database setups.

## Trust

- **Trust score (0–1):** 0.98
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/prajwalnayak7-redis)
- **Repository:** <https://github.com/prajwalnayak7/mcp-server-redis>

## 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": "prajwalnayak7-redis"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/prajwalnayak7-redis` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/prajwalnayak7-redis/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