How to Use the Upstash Redis MCP in Google ADK

Q: Can I limit key scanning in Upstash Redis for the Google ADK setup?

Absolutely. Use listkeys with a glob pattern; avoid the universal wildcard () on huge datasets to prevent performance slowdowns.

Let your Google ADK access and manipulate key/value data with enterprise reliability.

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Connect Upstash Redis MCP to Google ADK

Create your Vinkius account to connect Upstash Redis to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Upstash Redis with Google ADK

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Managing Counters in Google ADK

Use the `increment` tool to count things up or down. Your agent needs a simple, reliable way to track usage—this handles that perfectly. It's built for counting sessions or transactions.

Deleting Data with MCP Server

Need to clean out old data? The `delete` tool takes a comma-separated list of keys and wipes them out completely. This gives your agent explicit control over record retention policies.

Retrieving Key Information in Google ADK

Before acting, check the status first. The `get_key_info` tool tells you both the data type and if the key has an expiration time (TTL). Your agent gets this context before proceeding.

Setup guide

Set up Upstash Redis MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Upstash Redis tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Upstash Redis_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Upstash Redis tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Upstash Redis MCP in Google ADK

The MCP Server lets your agents interact directly with simple key-value data, supplementing the massive datasets in BigQuery. You can use it for fast lookups that don't need full SQL joins.

It acts as a high-speed cache and counter system, allowing your agents to maintain state or track metrics outside of the main BigQuery environment. It's all about speed.

It stores basic string values attached to keys. This keeps things simple and fast, which is exactly what you want when running large-scale enterprise agents.

Absolutely. Use `list_keys` with a glob pattern; avoid the universal wildcard (`*`) on huge datasets to prevent performance slowdowns.

This server touches key-value string data. Remember that while it's fast, you must implement your own security layers around this MCP Server.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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