MCP server for Redis, inspect keys, manage caches, and monitor performance
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TL;DR - Redis MCP Server
- Inspect and manage Redis from your AI assistant
- Check keys, values, TTLs, and memory usage
- No external API, connects to your Redis instance directly
Pricing: Free forever
Best for: Individuals & startups
Pros & Cons
Pros
- Debug Redis issues without memorizing CLI commands
- Direct connection, no external service
Cons
- Write operations available, scope access carefully
- Requires Redis connection URL
Key Features
Key inspection and searchValue read/writeCache management and flushingMemory and performance monitoring
Pricing Plans
Open Source
Free
- Full source code access
- Community support
- Self-hosted
What is Redis MCP Server?
Redis MCP Server lets your AI assistant inspect and manage Redis instances. Check keys, view values, flush caches, monitor memory usage, and debug caching issues, all through natural language.
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Redis MCP Server FAQ
What does Redis MCP Server do?
Redis MCP Server lets AI agents interact with Redis databases — getting and setting keys, managing data structures (lists, sets, hashes, sorted sets), running Lua scripts, and monitoring key patterns. Useful for debugging caches and managing session data.
How do I connect Redis MCP Server to my database?
Set the
REDIS_URL environment variable to your Redis connection string (e.g., redis://localhost:6379 or rediss://user:pass@host:port). The server connects on startup and exposes Redis commands as MCP tools.Is Redis MCP Server safe for production databases?
Exercise caution. The server can execute any Redis command including
FLUSHALL and DEL. For production use, connect with a read-only Redis replica or a user with restricted ACL permissions.Is Redis MCP Server free?
The MCP server is free and open source. Redis itself is open source (free) or available as Redis Cloud with a free tier (30 MB, 30 connections). Paid cloud plans start at $5/month.
What are good use cases for Redis MCP Server?
Debugging cache issues (inspecting keys, TTLs, values), managing feature flags stored in Redis, analyzing session data, monitoring pub/sub channels, and prototyping data structures before writing application code.
Source: github.com