Upstash Redis MCP. Manage Cache & State Without Leaving Your Chat Window
Upstash connects your serverless Redis database directly into any AI agent, letting you manage complex data structures and caching layers using plain conversation. You can run read/write operations—like fetching user sessions, incrementing counters, or managing message queues—without ever touching a command line or dedicated terminal client.
Claude 
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Cursor 
Gemini 
Windsurf 
VS Code 
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Vercel Give Claude and any AI agent real-world access
Set a value for a specific key or retrieve that value using simple read/write commands.
Store and access collections of related data, like user attributes or feature flags, within complex hash structures.
Use lists to add items to the end of a queue (right) or process them from the beginning (left), mimicking stack and queue behavior.
Maintain unique collections of identifiers, such as user IDs who have signed up for an event, ensuring no duplicates are stored.
Check if a key exists, see how long it has until expiration (TTL), or determine its data type.
Run multiple distinct commands—like getting three different values and then incrementing a counter—in a single request.
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What AI agents can do with Upstash Redis: 23 Tools for Data Management
Use these tools in your AI client to perform every common Redis operation—from simple key lookups to complex list management and batch executions.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Upstash MCPDecr
Decrements a numeric value associated with a key, useful for tracking limited resources or decreasing counts.
Del
Removes an entire key from the database; be careful because this action cannot be...
Exists
Quickly checks whether or not a specific data key is present in your Upstash Redis...
Expire
Sets an automatic deletion timer (TTL) on a key, ensuring temporary data cleans...
Get
Retrieves the simple string value associated with a given key name.
Hget
Pulls out one specific field's value from a structured hash record.
Hgetall
Retrieves every single field and its value contained within a full hash structure.
Hset
Adds or updates specific fields and values inside an existing structured hash key.
Incr
Increases a numeric counter value by one, useful for simple counting mechanisms.
List Keys
Lists keys in the database based on patterns or prefixes to help you audit what data...
Llen
Returns a count of how many elements are currently stored within a specific Redis...
Lpush
Adds new values to the beginning (left side) of a message queue list.
Lrange
Retrieves elements from a specific range within an ordered Redis list.
Pipeline
Executes many different database commands simultaneously in one call, improving...
Publish
Sends a message out to all listening subscribers on a specific channel, triggering...
Rpush
Adds new values to the end (right side) of a message queue list.
Sadd
Adds one or more unique items to a set, automatically ignoring any duplicates.
Set
Writes a new value to a key and optionally sets an automatic expiration time.
Sismember
Checks quickly if a unique member ID is already part of a specific set.
Smembers
Retrieves every single unique member ID that belongs to a given set.
Srem
Removes one or more specified members from a unique collection set.
Ttl
Checks how many seconds are left until a key automatically deletes itself.
Key Type
Identifies and reports the underlying data type of a given key (e.g., hash, list...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Claude AI
Open Claude Settings
Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
Add Custom Connector
Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:
https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp
Replace [YOUR_TOKEN_HERE] with your token
from cloud.vinkius.com. For OAuth-protected servers, expand
Advanced settings to add credentials.
Start a conversation
Open a new chat. The Upstash Redis integration is available immediately — no restart needed.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Upstash, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
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The Cache Layer Is Always Out of Reach
When you need to check a user's session data or update a feature flag, you currently have to context switch. You leave your development environment, open the Redis CLI in a separate terminal window, authenticate, manually type out commands like `HGETALL key:user:` and then copy-paste results into your ticket tracker.
With this MCP, that manual step disappears. You just ask your agent, 'What are all the fields for user 456?' Your agent runs the necessary command internally and delivers the formatted data right back to you in conversation.
Upstash Redis MCP Gives You Full Control Over Data Structures
Previously, managing structured data meant separate concerns. Updating a list required `LPUSH` or `RPUSH`. Tracking unique users meant running `SADD`. If you needed to combine these steps—say, adding three IDs and then reading the whole set—it was a multi-step chore across several tabs.
Now, your agent coordinates it all. You tell it: 'Add these five user IDs to the active group list.' It runs the `sadd` operation and confirms success instantly. Your AI acts as an in-memory data engineer.
What Upstash Redis MCP does for your AI
Connecting your Upstash Redis data store to an AI agent means treating it like an extension of your own memory. Instead of having to jump between chat interfaces and a separate database console, you simply ask your agent to perform actions on the cached data.
Your agent handles all the necessary complexity. You can tell it to check if a key exists, retrieve all fields from a user's session hash, or push messages onto a list for background processing. If you need to run multiple commands at once, like checking three different keys and then deleting one, your agent sequences them for you.
It’s about making the database an active participant in your workflow. This MCP is available across Vinkius, giving you access to this Redis power from any compatible client.
This functionality takes data management out of the terminal and right into the flow of natural conversation.
019d8496-4907-7232-bb59-ae5b7e9eaf04 
How to set up Upstash Redis MCP
The bottom line is that you treat your serverless Redis cache like an active, conversational source of truth for your entire application stack.
You connect your Upstash credentials (URL and Token) to the MCP within Vinkius.
Your AI agent interprets your natural language request, determining which Redis data operation is needed (e.g., 'get' or 'hset').
The MCP executes the command against your live database and returns the resulting data directly to your chat interface.
Who uses Upstash Redis MCP
This MCP is essential for developers and operations teams who need to interact with cached data structures without context switching. If you're tired of opening a separate terminal just to check if a feature flag was set or how many times a counter ticked, this tool saves you time.
Managing session storage, rate limiting counters, and temporary state data structures directly from the chat interface during development.
Auditing database health by checking key patterns or setting time-to-live (TTL) expirations on critical configuration keys across environments.
Manipulating complex application state, such as user roles and permissions stored in hash records, to test application logic before deployment.
Benefits of connecting Upstash Redis MCP
You avoid complex data flow by using sadd or smembers. Instead of writing code to maintain unique user lists, you simply ask your agent to manage the set membership.
Rate limiting becomes trivial. You can use incr and decr in conversational prompts to track usage counts instantly, making it easier to enforce business logic without adding boilerplate code.
Auditing data structure health is fast. Use list_keys or key_type to see what keys exist and confirm they are stored as the expected hash format when debugging a session problem.
Batch operations are simplified with the pipeline tool. Instead of sending five separate requests, you ask your agent to run them all at once for maximum efficiency.
Data lifecycle management is automatic. Setting an expiration using expire ensures that temporary keys—like shopping cart states—are deleted without manual cleanup tasks.
Upstash Redis MCP use cases
Debugging a broken user session
A full-stack developer notices user data is corrupted. They ask their agent to use hgetall on the relevant session key and then run key_type to confirm the structure, instantly pinpointing if it's stored incorrectly.
Implementing a simple message queue
An operations engineer needs background processing. They use rpush to add tasks to a queue list and then have their agent process them using lrange or pop, completely bypassing the need for dedicated worker services.
Tracking feature flag rollout
A backend developer wants to test new features on specific users. They use set to write a unique key like 'feature:v2:user123' and then set a short TTL using expire, guaranteeing the flag expires after testing.
Building an event notification system
A team needs multiple services to react when user data changes. They use publish on a central channel, allowing any listening service (like logging or email) to automatically respond without direct coupling.
Upstash Redis MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Manual CLI Context Switching
Having to open up the Upstash web dashboard, manually type HGETALL user:123, wait for the result, then switch tabs to run EXPIRE user:123 3600.
Instead, ask your agent directly: 'Get all data from user:123 and set its expiry to one hour.' The agent executes both hgetall and expire sequentially for you.
Over-relying on single operations
Telling the agent simply to 'change the user status'. This might only execute a basic set, forgetting that the key needs an expiration or multiple fields need updating.
Be specific: 'Update the user's profile hash by setting their email and then set the entire record to expire in 24 hours.' Use hset combined with expire.
Forgetting transactional needs
Trying to increment a counter, check its type, and then delete it using three separate commands. If one fails, the whole process breaks.
Use the pipeline tool. Ask your agent: 'Run this sequence: get the current count, increment it by 1, and confirm the new value.' This guarantees all steps run together.
When to use Upstash Redis MCP
You need this MCP if your primary pain point is interacting with Redis data structures (hashes, sets, lists) without opening a terminal. If you mostly just need simple key-value lookups and don't care about complex structures or workflows, a basic key-value tool might suffice. However, because Upstash handles specialized types like Lists and Sets, this MCP shines when your application state is complex—think session management, message queues, or feature flag systems. Don't use this if you need to manage data in a relational database (SQL); that requires an entirely different connection. But if your stack is built on microservices using Redis for caching or queuing, this is the right tool.
Frequently asked questions about Upstash Redis MCP
How do I check if a key exists using Upstash Redis MCP? +
You use the 'exists' tool to quickly confirm key presence without retrieving any value. This is great for pre-checking data before attempting a read or write operation.
Can I run multiple commands at once with Upstash Redis MCP? +
Yes, you use the 'pipeline' tool to execute several commands in one request. This saves time and is essential for efficient batch updates across your data structure.
What is the difference between `incr` and `set` with Upstash Redis MCP? +
incr automatically increases a numeric counter by one, ensuring atomic counting. The 'set' tool simply writes a new value or overwrites an existing string value.
How do I delete data safely using Upstash Redis MCP? +
Use the 'del' tool to remove keys entirely. However, remember that this action is irreversible, so always confirm which key you are deleting first.
Does Upstash Redis MCP support message queuing? +
Yes, it supports queue patterns using lists. You can add items with 'rpush' and then process them by retrieving ranges or popping the elements out of the list.