🔥 wredis-mcp

Transform your AI Agents into expert WRedis Architects.

wredis-mcp is a professional Model Context Protocol (MCP) server that bridges the gap between AI Agents (Claude, Gemini, OpenCode) and WRedis. It empowers agents to search, design, and deploy high-performance Redis-backed services following strict industry-standard patterns.

✨ Key Features

• 🔍 Expert Pattern Catalog: Query production-ready patterns across all WRedis data structures (Hash, Queue, Stream, Pub/Sub, SortedSet, Geo, Bitmap, HyperLogLog, Pipeline, Transaction, Cache, HA).

• 🏗️ Strict Architecture Enforcement: Guides AI to output clean code using mandatory config/, cache/, repositories/, and main.py folder structures.

• 📘 Architect's Manual: Built-in expertise for Monolith-to-Redis refactoring, TTL management, key naming, and atomicity patterns.

• 💻 Unified CLI: Manage your MCP service with simple commands: run, start, stop, and config.

• 🛡️ Privacy First: 100% local execution via stdio or SSE.

Related MCP server: Tyra Advanced Memory MCP Server

🚀 Quick Start

1. Installation

Clone the repository and run the automated installer, or install via pip:

pip install -e .

2. Integration

Get your agent-specific configuration block and installation commands by running:

wredis-mcp config

The CLI will dynamically detect your Python environment and provide exact copy-paste commands for Gemini CLI (e.g. gemini mcp add ...) and JSON blocks for Claude Desktop.

🛠️ CLI Usage

🛠️ MCP Tools

📂 Project Structure

• src/wredis_mcp/: Core server logic and tools.

• src/wredis_mcp/catalog.py: Pattern catalog synchronization with local fallbacks.

• src/wredis_mcp/templates.py: Professional boilerplate definitions.

• examples/: Sample implementations and use cases.

📄 License

MIT License - Crafted with ❤️ by William Rodriguez (wisrovi).