How to Install Upstash MCP in OpenAI Agents SDK
Serverless Redis and Kafka — manage caches, rate limits, and queues via AI with pay-per-use pricing
What Upstash MCP does
Upstash MCP gives AI agents access to serverless Redis and Kafka — perfect for managing caches, rate limiting, queues, and real-time event streaming in serverless applications. Features: Redis: - Get, set, and delete keys with full TTL support - Work with all Redis data types: strings, lists, hashes, sets, sorted sets - Inspect key patterns and database statistics - Manage multiple databases across regions - Flush databases and manage persistence Kafka: - Create and manage topics - Inspect consumer group lag - Monitor throughput and message rates Particularly valuable for applications using Context7 MCP (also by Upstash) — manage the Redis cache powering your documentation layer directly from Claude. Pay-per-request pricing — zero idle cost. Perfect for AI workloads that run intermittently.
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="npx",
args=["-y", "@upstash/mcp-server"],
env={
"UPSTASH_REDIS_REST_URL": "https://...",
"UPSTASH_REDIS_REST_TOKEN": "your_token",
},
)
agent = Agent(
name="My Agent",
model="gpt-4o",
mcp_servers=[mcp_server],
)Install in other clients
For maintainers
If you maintain Upstash MCP, add this badge to your README to show it's verified on CuratedMCP:
[](https://curatedmcp.com/marketplace/upstash-mcp)