Official Redis server — search keys, inspect data structures and manage caches in natural language.
The Redis MCP server is maintained by Redis themselves, and it shows in the coverage: rather than a thin GET/SET wrapper, it speaks the full breadth of Redis data structures — strings, hashes, lists, sets, sorted sets, streams, JSON documents and even vector search indexes. If your team uses Redis as more than a cache, that breadth matters.
The everyday use is operational spelunking. Redis instances accumulate mystery keys the way attics accumulate boxes, and "what's actually in this cache?" is suddenly a question you can ask directly: scan for patterns, inspect a hash's fields, check a key's TTL, eyeball a stream's recent entries. Debugging a stale-cache bug becomes "look up the session key for this user and tell me when it expires" instead of a round of redis-cli archaeology.
Because it can write as well as read, it also covers routine operations — clearing a poisoned cache entry, seeding test data, bumping a TTL — though that same power means you should scope its credentials carefully. A Redis ACL user limited to the commands and key patterns you're comfortable with is the right way to run this anywhere near production; DEL on the wrong pattern has ruined better days than yours.
It's Python-based, installable via uvx or Docker, and connects to anything Redis-compatible: local instances, Redis Cloud, clusters with TLS. For teams on Redis Cloud there's also a managed remote variant, which drops the local process entirely.
ACL SETUSER mcp on >secret ~cache:* +@read limits it to a key prefix and read commands, so FLUSHALL isn't even in its vocabulary.SCAN rather than KEYS, so it won't block the server, but a wildcard pattern across a million-key instance is still a long sequence of round trips.info keyspace section before drawing conclusions about memory: the count of keys without a TTL is usually where unexplained growth is hiding.Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.
Find the exact key behind a stale-data bug, check its TTL and contents, and clear it — conversationally.
Survey what key patterns exist, what's eating memory, and what has no expiry set.
Use Redis structures (and vector search) as fast working memory for agent workflows.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| scan_keys | Scan for keys matching a pattern without blocking the server |
| get / set | Read and write string values with optional expiry |
| hget_all / hset | Inspect and modify hash fields |
| list / set / zset operations | Work with lists, sets and sorted sets |
| json_get / json_set | Read and write RedisJSON documents |
| xrange | Read entries from Redis streams |
| vector_search | Query vector indexes for similarity search |
| info | Server info: memory, clients, keyspace statistics |
{
"mcpServers": {
"redis": {
"command": "uvx",
"args": ["--from", "redis-mcp-server", "redis-mcp-server",
"--url", "redis://localhost:6379/0"]
}
}
}Use rediss:// URLs for TLS connections to managed Redis.
Python 3.13+ with uv, or Docker. Network access to your Redis instance; use a scoped ACL user near production.
| Variable | Description | Required |
|---|---|---|
| REDIS_URL | Connection URL as an alternative to the --url flage.g. rediss://user:pass@host:6380/0 | Optional |
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