How to Install Redis MCP in OpenAI Agents SDK
Connect AI agents to Redis — get, set, and manage cached data, queues, and pub/sub channels
What Redis MCP does
Full Redis access for AI agents — work with all Redis data structures, manage expiration, inspect keys, and handle real-time pub/sub messaging through natural language. Features: - String operations: GET, SET, MGET, MSET with TTL support - List operations: LPUSH, RPOP, LRANGE — build queues and stacks - Hash operations: HSET, HGET, HGETALL for structured data - Set operations: SADD, SMEMBERS, SINTER for unique collections - Sorted sets: ZADD, ZRANGE for leaderboards and time-series - Key management: KEYS, SCAN, TTL, PERSIST, DEL - Pub/Sub: subscribe to channels, publish messages - Transactions: MULTI/EXEC for atomic operations - Lua scripting support Works with Redis, Redis Cluster, Redis Sentinel, and Redis-compatible services (Upstash, AWS ElastiCache, Azure Cache for Redis). Ideal for AI agents managing application state, session data, rate limits, and real-time queues.
Installation steps
- 1Install: pip install openai-agents
- 2Copy the snippet below into your agent code
- 3Replace placeholder env values with your real keys
- 4Pass mcp_servers=[mcp_server] to your Agent()
Python snippet
from agents import Agent
from agents.mcp import MCPServerStdio
mcp_server = MCPServerStdio(
command="uvx",
args=["mcp-server-redis"],
env={
"REDIS_URL": "redis://localhost:6379",
},
)
agent = Agent(
name="My Agent",
model="gpt-4o",
mcp_servers=[mcp_server],
)Install in other clients
For maintainers
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