Kuwait Payments (Tap Payments — KNET)
Server Details
Kuwait payments for AI agents — KNET via Tap Payments. Never holds funds.
- Status
- Unhealthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.3/5 across 3 of 3 tools scored.
The three tools serve clearly distinct purposes: creating a payment link, querying its status, and issuing a refund. There is no overlap or ambiguity.
All tool names follow a consistent verb_noun pattern: create_payment_link, query_payment_status, refund_payment. The naming is predictable and clear.
Three tools is appropriate for a focused payment server covering creation, status checking, and refunds. The count is not excessive nor insufficient.
The set covers the essential lifecycle of a payment link: create, check status, refund. Missing cancellation before payment, but the automatic completion reduces need. Minor gap.
Available Tools
3 toolscreate_payment_linkAInspect
Create a payment link in KWD for Kuwait via Tap Payments. Buyer pays with KNET (the Kuwaiti debit network), cards, Apple Pay — whatever is enabled on the Tap account. Returns a hosted checkout URL the buyer opens to pay — payment completes automatically, no confirm step. Bring your own credentials via HTTP header (x-tap-secret-key; free test credentials from businesses.tap.company never move real money). Money always flows buyer→Tap Payments→merchant; this service never touches funds.
| Name | Required | Description | Default |
|---|---|---|---|
| amount_kwd | Yes | Amount in KWD (decimals allowed), e.g. 5.0. Minimum 0.5. | |
| description | Yes | What this payment is for (shown to the buyer, ≤200 chars) | |
| success_url | No | Optional https URL to send the buyer to after payment. | |
| reference_id | No | Your unique order reference (≤40 chars). Auto-generated if omitted. | |
| customer_email | Yes | Buyer email (required by Tap Payments; the receipt goes there). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses important behaviors: write operation (create), automatic payment completion (no confirm step), money flow (buyer->Tap->merchant, service never touches funds), and authentication via x-tap-secret-key. These add context beyond annotations which only show readOnlyHint=false and destructiveHint=false.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is 4 sentences, front-loaded with the core purpose, and each sentence adds new information without redundancy. It's efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters (3 required) and no output schema, the description covers return value (hosted checkout URL), authentication method, and behavioral details. It doesn't require additional context for the agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description adds useful elaboration: for amount_kwd it gives an example (5.0), for description it mentions 'shown to buyer' and character limit, for reference_id it notes auto-generation, for customer_email it explains 'required by Tap Payments' and 'receipt goes there'. This adds significant value over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Create a payment link in KWD for Kuwait via Tap Payments.' It specifies the currency, payment methods, and the output (hosted checkout URL). It naturally distinguishes from siblings (query_payment_status, refund_payment) by focusing on creation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: buyer pays with KNET, cards, Apple Pay, no confirm step, and credentials via header. It implies when to use (need payment link creation) but doesn't explicitly compare to alternatives or state when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_payment_statusARead-onlyInspect
Check whether a Kuwait payment (created by create_payment_link) has been paid. Queries Tap Payments directly — pull-based, no webhook needed. paid=true when status is PAID.
| Name | Required | Description | Default |
|---|---|---|---|
| charge_id | Yes | The charge_id (chg_...) returned by create_payment_link |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint and openWorldHint. The description adds value by specifying the pull-based nature and the condition for 'paid=true', aligning with readOnlyHint and providing transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff, front-loaded purpose and scope, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks information about the return value structure, error handling, or behavior for non-existent payments. For a simple query tool, it is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the charge_id parameter well (100% coverage). The description does not add extra semantics for the parameter beyond what the schema provides, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks payment status for Kuwait payments created by create_payment_link, with a specific verb ('Check') and resource ('payment status'), distinguishing it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context (pull-based, no webhook needed) implying when to use it, but lacks explicit guidance on when not to use or alternatives. Siblings are clearly different actions, so context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
refund_paymentADestructiveInspect
Refund a paid payment (created by create_payment_link). Full refund by default; pass amount for a partial refund where supported. Refunds respect the same owner policy guardrails (x-agentpay-max-amount) as payments — the amount is checked before anything is sent to the gateway.
| Name | Required | Description | Default |
|---|---|---|---|
| amount | No | Optional partial-refund amount in the local currency major unit. Omit for a full refund. | |
| charge_id | Yes | The charge_id of the paid payment (same id used by query_payment_status) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark destructiveHint=true and readOnlyHint=false. The description adds that refunds respect owner policy guardrails and the amount is checked before gateway processing. This provides useful behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states action and limitation (to payments from create_payment_link), second adds details on partial refund and guardrails. No fluff, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should have mentioned return value or side effects. It mentions guardrails but omits what happens after refund (e.g., response format). Adequate but incomplete for an action that may need feedback.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with descriptions. The description reiterates that amount is optional for partial refund. No additional semantics beyond schema. Given 100% coverage, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool refunds a paid payment, created by create_payment_link. It specifies full refund by default and optional partial refund. This distinguishes it from siblings (create_payment_link and query_payment_status) which are for creation and status queries respectively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates usage context: only for payments created by create_payment_link. It mentions the guardrails check but does not explicitly state when not to use or alternatives. However, given the siblings, the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!