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.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.
| 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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