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Open Loyalty AI Labs  /  Project No. 02

Run your loyalty program by asking.

The Open Loyalty MCP server connects Claude, Cursor, and any MCP client straight to your loyalty engine. Describe what you want in plain language. The agent does the work. Your team keeps the judgment.

$ npx -y @open-loyalty/mcp-server Copy
Works with · Claude Desktop · Claude Code · Cursor · any stdio MCP client
Agent sessionconnected
YouSet up double points this weekend for members who haven’t bought in 60 days.
segments.createLapsed 60d✓ 4,182 members
campaigns.create2× points · Fri–Sun✓ drafted
campaigns.previewimpact estimateawaiting you
Structured result
campaign_idcmp_7f2amultiplier2audience4182statusawaiting_approval
Nothing goes live until a human approves.

Plain language in. Real changes out.

No endpoints to learn, no payloads to assemble. You describe the outcome, the agent maps it to real API calls, and you stay in control of what ships.

01

You describe it

Ask in the words you’d use with a colleague. “Reward members who refer a friend.” No technical translation on your side.

02

The agent calls the right tools

It maps your request to real Open Loyalty calls like segments.create or campaigns.create across 19 domains, and shows its work.

03

You approve, it ships

The agent proposes the change with a structured result. Nothing touches your live program until a human signs off.

112 tools. 19 domains. One npx command.

Because Open Loyalty was API-first from day one, the whole platform is already addressable. The MCP server hands all of it to the agent, not a demo slice of it.

What your team can ask for.

Real prompts from our own testing. The agent translates each into the right calls against your live program.

YouWhich tier has the weakest retention this quarter?

Agent + Open LoyaltyPulls program analytics, compares retention by tier, and surfaces the one slipping the most.

YouAdd 500 points to this member and confirm the new balance.

Agent + Open LoyaltyIssues the points through the API and reads back the updated wallet balance.

YouDraft an achievement for first-time referrers.

Agent + Open LoyaltyProposes the achievement rules and reward, ready to publish once a human signs off.

YouSet up double points this weekend for lapsed members.

Agent + Open LoyaltyBuilds the segment, drafts a time-boxed campaign, and holds it for your approval.

Powerful, but never off the leash.

The agent operates inside the same boundaries your team does. You decide what it can reach, and you see everything it does.

Scoped to your token

It acts through your API token and store scope. It only reaches what you allow.

Human in the loop

Changes are proposed and held for approval, not silently executed.

Every call is auditable

These are standard API calls, logged and traceable like any other request.

Runs locally

Server runs over stdio, the standard MCP transport. Nothing to host for local use.

Why it covers everything

The API was the product. That’s why this works.

We didn’t bolt an AI feature onto loyalty. We built an engine an agent can operate end to end: members, points, tiers, rewards, campaigns, segments, analytics. That starting point is why the MCP server reaches the whole platform, not a corner of it.

The whole loyalty stack, addressable.

112 tools across 19 domains. If it lives in the Open Loyalty API, an agent can reach it.

Members10
Points6
Tier Sets6
Rewards9
Campaigns12
Segments9
Achievements7
Badges4
Analytics9
Transactions4
Webhooks6
+ Stores, Import, Export, ACL, API Keys, Audit Logs, Wallet Types, Rolesadmin

Connect once with npx -y @open-loyalty/mcp-server and three values: your API URL, an API token, and a default store code. That scopes everything the agent can touch.

MCP is how we make the whole platform agent-native.

Steve proved AI can verify the real world for loyalty. The MCP server is the other half: giving an agent the controls to act on it. Both started here in AI Labs. The next one starts with your challenge.

Give your loyalty program to an agent.

Open source, MIT licensed, live on npm. Connect it to your AI client and start asking.