Where do I locate my Upstash REST URL and Token?

Sign into your Upstash management console and load your specific Redis cluster. Scroll down visually on the main 'Details' page until you hit the 'REST API' section block. You will see both your 'UPSTASH_REDIS_REST_URL' and the alphanumeric 'UPSTASH_REDIS_REST_TOKEN' ready to be copied.

Can the agent interact with standard Redis connections (redis://)?

No, this specific MCP connection module specifically utilizes Upstash's serverless HTTP/REST endpoints. It bypasses conventional persistent TCP Redis sockets to provide highly secure and connection-agnostic read/write integrations optimized for AI servers.

Are there limitations to wildcard patterns when doing list_keys?

Yes, standard Redis operational caveats apply. Searching broadly via a '*' (asterisk) scan across massively populated environments isn't recommended. Aim to request the AI narrow down patterns, like 'session:*' instead of blank wildcards.

Upstash Redis MCP Server for OpenAI Agents SDK 7 tools — connect in under 2 minutes

Name: Upstash Redis
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 7 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Upstash Redis through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Upstash Redis Assistant",
            instructions=(
                "You help users interact with Upstash Redis. "
                "You have access to 7 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Upstash Redis"
        )
        print(result.final_output)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Upstash Redis MCP Server

Connect your Upstash Redis serverless database securely to your conversational AI agent via their REST API. Activating this integration grants your AI the technical autonomy to function as a responsive database administrator, enabling it to scan live keys, read raw datastore strings, set temporal expiration values, and even debug in real-time straight from your chat or IDE terminal.

The OpenAI Agents SDK auto-discovers all 7 tools from Upstash Redis through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Upstash Redis, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Read & Write Values — Fetch the exact string configuration of a stored key (get), or instruct the AI to inject a new value (set) complete with Time-To-Live (TTL) expiration limits.
Data Structure Discovery — Perform pattern-based scans across your database to track down dynamically generated keys and inspect their underlying structures or lifespans (list_keys, get_key_info).
Manage Counters — Safely increment or decrement numerical keys dynamically, perfect for managing rate limits, operational counters, or user session metrics directly during troubleshooting flows.
Maintain Health — Ping the cluster instance for responsive status checks and remove (delete) specific keys or cache fragments completely.

The Upstash Redis MCP Server exposes 7 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Upstash Redis to OpenAI Agents SDK via MCP

Follow these steps to integrate the Upstash Redis MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 7 tools from Upstash Redis

Why Use OpenAI Agents SDK with the Upstash Redis MCP Server

OpenAI Agents SDK provides unique advantages when paired with Upstash Redis through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Upstash Redis + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Upstash Redis MCP Server delivers measurable value.

Automated workflows: build agents that query Upstash Redis, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Upstash Redis, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Upstash Redis tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Upstash Redis to resolve tickets, look up records, and update statuses without human intervention

Upstash Redis MCP Tools for OpenAI Agents SDK (7)

These 7 tools become available when you connect Upstash Redis to OpenAI Agents SDK via MCP:

delete

Provide a comma-separated list of keys. Deletes one or more keys from Redis

get

Retrieves the string value stored at a key

get_key_info

Retrieves the data type and TTL of a key

increment

Use negative numbers to decrement. Increments or decrements a numeric counter at a key

list_keys

Avoid broad patterns like "*" on large databases. Scans for keys matching a glob pattern

ping

Pings the Redis instance to verify connectivity

set

You can specify expiry in seconds. Sets a string value at a key with an optional TTL

Example Prompts for Upstash Redis in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Upstash Redis immediately.

"List all active Redis keys associated with app sessions."

"Check the Time-To-Live duration limit configured for the 'cache:product_header' key."

"Delete all caching strings tagged as 'user_193_avatar' from the database immediately."

Troubleshooting Upstash Redis MCP Server with OpenAI Agents SDK

Common issues when connecting Upstash Redis to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Upstash Redis + OpenAI Agents SDK FAQ

Common questions about integrating Upstash Redis MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.