Zinrelo MCP. Automate point accrual and member status tracking.
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Zinrelo connects your AI agent directly to a loyalty program. It lets you automate member enrollment, award points for purchases or activities, track transactions, and manage reward redemptions using natural language commands.
What your AI agents can do
Award points activity
Grants points to a member because they completed a custom, non-purchase action (e.g., signing up for a contest).
Award points purchase
Adds points to a member's account based on the value of a recorded purchase.
Deduct points
Manually removes points from a user when necessary (e.g., for returns or corrections).
Retrieve a specific customer's detailed loyalty profile, including their tier level and current balance.
Pull a full list of every active loyalty program participant in the system.
Automatically grant point credits based on a recorded sale amount or transaction ID.
List a member's entire historical record, showing every time they earned or spent points.
Create or update a customer's loyalty profile record in the system.
Process the exchange of accumulated points for a defined reward (like a coupon).
Ask AI about this MCP
Supported MCP Clients
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Zinrelo: 9 Tools for Loyalty Program Management
Use these nine tools to manage every aspect of your loyalty program—from enrolling new members to processing complex point deductions.
019d7628award points activity
Grants points to a member because they completed a custom, non-purchase action (e.g., signing up for a contest).
019d7628award points purchase
Adds points to a member's account based on the value of a recorded purchase.
019d7628deduct points
Manually removes points from a user when necessary (e.g., for returns or corrections).
019d7628enroll member
Creates a new loyalty profile record for a customer, or updates an existing one.
019d7628get loyalty settings
Retrieves high-level configuration details about the overall point program rules and settings.
019d7628get member details
Pulls all current information for a specific member, including their tier status and balance.
019d7628list loyalty members
Returns a full list of every individual registered in the loyalty program.
019d7628list member transactions
Fetches the complete chronological history of point earnings and spending for one member.
019d7628redeem reward
Processes the exchange, using points to fulfill a specific reward or coupon request.
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.
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Make Your AI Do More
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- Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector
You connect your AI agent directly to Zinrelo so it handles all your loyalty and rewards stuff from plain language commands. You don't gotta jump through five different dashboards just to manage a member profile or process a coupon. Your agent does the heavy lifting.
Need to get people in the system? You can use the agent to enroll new members, creating or updating their full loyalty profiles with one command. If you need to see who's actually playing the game, your agent pulls a list of every single registered participant right out of the program.
Once you have that list, you can pull up any specific member’s entire profile—that includes checking their current tier status and seeing exactly how many points they've got saved up.
When it comes to earning points, the server handles two main types of credits. If a customer makes a purchase, your agent adds points based on that recorded sale amount or transaction ID using award_points_purchase. But wait, they might not have bought anything yet; maybe they signed up for a contest or completed some other custom action.
For those instances, you tell the agent to grant them points specifically for that activity via award_points_activity.
When someone needs to spend their credits, your agent processes the entire exchange using redeem_reward, taking accumulated points and fulfilling whatever coupon or reward they want. If a return comes through, or if you spot an error on the ledger, you use deduct_points to manually remove points when necessary. You're in total control of point adjustments.
If someone asks, "How did I get all these points?" your agent fetches that member's entire history using list_member_transactions, showing every single time they earned or spent a dime. For high-level oversight, you can check the master settings—the overall rules and configuration details for the point program itself by calling get_loyalty_settings.
You never gotta worry about getting lost in the fine print because your agent manages it all.
Seriously, it's simple: Tell your agent what needs doing. Whether you need to audit transactions across the board or just check a single person's balance and tier status using get_member_details, it executes the function instantly. It takes the complexity out of loyalty management so you can actually focus on running the business.
How Zinrelo MCP Works
- 1 Subscribe to the server and supply your Zinrelo Partner ID and API Key.
- 2 Give your AI client instructions, like 'Check John Doe's balance.'
- 3 The agent uses the correct tool (e.g.,
get_member_details) and returns structured data you can use immediately.
The bottom line is you tell your agent what to do; it handles the API calls to Zinrelo, bypassing manual logins and dashboard navigation entirely.
Who Is Zinrelo MCP For?
Marketing Managers need this when they can't manually track who earned points for a special campaign. Customer Support reps use it when they need to instantly verify a customer's balance or transaction history during an active chat session. E-commerce Owners rely on it to automate enrollment and point tracking without building custom integrations.
Quickly checks a customer’s current point total or reviews their last ten transactions during an interaction.
Runs reports to see member growth and triggers mass point awards for campaign participants.
Automates the onboarding process for new customers and validates reward activity after a sale.
What Changes When You Connect
- Instantly calculate rewards. Instead of navigating to a separate ledger, your agent uses
get_member_detailsto pull the current balance in milliseconds, giving you real-time visibility into eligibility. - Process transactions without friction. When an item sells, trigger
award_points_purchase. The agent handles the API call immediately, ensuring points are credited right alongside the sale record. - Build a complete audit trail. Use
list_member_transactionsto pull every single point movement—earnings and deductions—allowing you to verify any claim instantly for both support and compliance purposes. - Manage membership on the fly. Need to onboard someone? Run
enroll_member. Your agent handles the data validation and record creation, so you don't have to manually enter details into a form. - Handle corrections easily. If a mistake happens, use
deduct_pointsinstead of waiting for a manual review process. It keeps your point economy accurate when things go sideways.
Real-World Use Cases
Handling a large group sign-up event
A marketing team hosts an event and 20 people attend. Instead of manually creating twenty records, the agent runs enroll_member for all attendees and then uses award_points_activity to give them a bulk bonus point package immediately after check-in.
Customer support needs to verify eligibility
A customer calls asking about a discount. The agent runs get_member_details. It pulls the current tier status and points balance, allowing the representative to confirm if they qualify for a reward or deduction before leaving the chat window.
Fixing an accounting error
The system incorrectly awarded 100 points. Instead of opening a ticket and waiting, the agent runs deduct_points directly via natural language command, correcting the balance instantly while logging the action.
Processing an online sale
A purchase completes for $250. The e-commerce backend tells your AI client to run award_points_purchase. The agent calls the function, and the customer's points are credited instantly, closing the loop on the transaction.
The Tradeoffs
Trying to use a general database search
The user tries to find a balance by running a generic 'search member' query that returns unstructured data, forcing them to manually cross-reference point totals with transaction history.
→
Always start with get_member_details or list_member_transactions. These tools pull structured, confirmed data directly from Zinrelo, eliminating guesswork.
Ignoring the existing program rules
A user tries to manually award points without checking if the member is eligible for that activity type, leading to point discrepancies and distrust.
→
First run get_loyalty_settings to understand the current program constraints. Then, use specific tools like award_points_activity or award_points_purchase only when those rules are met.
Running too many sequential calls
The agent runs list_loyalty_members, then tries to process all of them individually using get_member_details, which is slow and costly.
→
If you need a list, use list_loyalty_members first. If you only care about one person, go straight to get_member_details—don't waste time listing everyone else.
When It Fits, When It Doesn't
Use this server if your primary goal is managing a structured, point-based loyalty model where transactions (purchases, activities) directly correlate with quantifiable points. It works best for e-commerce and marketing automation systems that need constant, verifiable ledger updates.
Don't use it if your loyalty system relies on non-point mechanics, like status access or exclusive content that can't be quantified by a point count. For those models, you might need an alternative integration focused on permissions or access control rather than transactional finance. If your core metric isn't 'points balance,' this server won't solve the underlying retention problem, even if it handles the data flawlessly.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zinrelo. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 9 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Checking a customer’s points status usually means logging into three different systems.
Today, checking a customer's loyalty standing is a painful dance. You log into the CRM to find their profile, then jump to the e-commerce platform to see purchase history, and finally go to the rewards dashboard just to confirm their current point balance. It takes three tabs open and five minutes of copy/pasting.
With the Zinrelo MCP Server, you ask your agent one question: 'What's John Doe's status?' The agent runs `get_member_details` and consolidates everything—tier, points, history—into a single, immediate answer. It’s that simple.
The Zinrelo MCP Server lets you automate point awarding with `award_points_purchase`.
Before this tool, every time a sale closed, an ops person had to manually log into the loyalty system and run a script or enter a bonus point amount. This was slow; errors were common, and points often lagged behind sales data.
Now, your agent handles it automatically. As soon as a purchase is recorded, `award_points_purchase` fires, updating the member's balance in real-time. The system moves from reactive logging to proactive point management.
Common Questions About Zinrelo MCP
How do I check if a member exists before awarding points with `award_points_activity`? +
You should run get_member_details first. This verifies the customer ID and ensures their profile is active in Zinrelo. If that call fails, you know where to stop.
Is there a way to list all members using the Zinrelo MCP Server? +
Yes, use list_loyalty_members. This function pulls every member ID and basic status. It's useful for running bulk reports or finding users who haven't engaged recently.
What if I need to correct points manually? Should I use a different tool than `deduct_points`? +
No, deduct_points is the right tool for manual corrections. It logs the deduction and requires input on why it's happening, which maintains your audit trail integrity.
Does Zinrelo MCP Server handle complex reward redemption logic? +
The redeem_reward tool processes the point transfer for a defined reward. However, if your rewards require multiple steps (e.g., check tier first, then deduct points), you'll need to coordinate several calls.
When I use the `enroll_member` tool, what mandatory data fields do I need to provide? +
You must supply a unique member identifier and the customer's primary email address. The API validates these two fields first; other details like name are optional but recommended.
If `get_member_details` runs for an invalid user ID, how should I handle the error? +
The tool returns a 404 status code and a specific JSON payload indicating 'Member Not Found.' Your agent can catch this structured response to tell the user exactly why the lookup failed.
What is the best sequence of calls if I need to record both enrollment and points using `enroll_member` and `award_points_activity`? +
You should always call enroll_member first. This ensures the member profile exists before trying to attach any transaction data, making your workflow reliable.
Does `list_member_transactions` handle pagination if a loyalty member has hundreds or thousands of records? +
Yes, it supports standard offset and limit parameters. You pass the desired page number and size to retrieve large history sets efficiently without hitting data limits.
How do I award points for a specific activity? +
Use the award_points_activity tool with the member's email and the specific activity_id defined in your Zinrelo dashboard.
Can I see a history of point redemptions for a user? +
Yes, the list_member_transactions tool retrieves a complete history of all point earnings and redemptions for a target member.
Is it possible to manually deduct points? +
Absolutely. Use the deduct_points tool to remove a specific amount of points from a user's loyalty balance.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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