Oman Payments (Tap Payments — cards / Apple Pay)
Server Details
Oman payments for AI agents — cards / Apple Pay via Tap Payments. Never holds funds.
- Status
- Healthy
- 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 4.2/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: creating a payment link, querying its status, and processing a refund. There is no overlap or ambiguity.
All three tools follow a consistent verb_noun pattern using snake_case (create_payment_link, query_payment_status, refund_payment), making the set predictable and easy to navigate.
With 3 tools, the server is well-scoped for its purpose of handling basic payment operations via Tap Payments. Each tool earns its place and the count falls within the ideal range of 3-15.
The set covers the core payment lifecycle: create, query, and refund. A minor gap exists—no tool to cancel or void an unpaid payment link—but agents can work around it (e.g., via expiry). Overall, the surface is reasonably complete for the stated domain.
Available Tools
3 toolscreate_payment_linkAInspect
Create a payment link in OMR for Oman via Tap Payments. Buyer pays with 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_omr | Yes | Amount in OMR (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?
Goes beyond annotations by explaining money flow (buyer→Tap Payments→merchant), that no funds are touched internally, and the automatic completion without confirm step. Also clarifies test credentials behavior. Annotations already indicate openWorldHint and non-readOnly, and description adds valuable behavioral context.
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?
Concise and front-loaded: first sentence states purpose and region. No redundant sentences. Every sentence adds value (authentication, payment flow, no confirm step).
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?
Provides sufficient context for an AI to understand purpose, behavior, and required setup. Lacks details on error handling or rate limits, but these are not critical for a creation tool with clear schema descriptions and annotations.
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 descriptions cover all 5 parameters (100% coverage), so baseline is 3. The tool description adds overall context but does not enhance individual parameter meanings beyond what the schema provides. No parameter-specific details in description.
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?
Clearly states the tool creates a payment link for Oman via Tap Payments. The verb 'create' and specific resource 'payment link' are explicit, and it distinguishes from sibling tools 'query_payment_status' and 'refund_payment' by focusing on generation, not query or refund.
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?
Provides context on when to use (to initiate a payment), payment methods (cards, Apple Pay), and authentication (x-tap-secret-key). Implicitly separates from siblings but could explicitly state not to use for refunds or status queries.
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 Oman 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 already provide readOnlyHint=true and openWorldHint=true. The description adds minimal behavioral context ('paid=true when status is PAID') but does not elaborate on side effects, error states, or rate limits. No contradiction with 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 with no extraneous information, front-loaded with the main purpose. Every sentence earns its place.
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 adequately covers the core function and output, but lacks details on error handling (e.g., invalid charge_id) or a full description of the response structure. Since no output schema exists, more detail would be beneficial.
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 coverage is 100% for the single parameter. The description adds valuable context by specifying that charge_id is returned by create_payment_link, which goes beyond the schema's generic string description.
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 Oman payments created by create_payment_link. It uses a specific verb and resource, and distinguishes itself from sibling tools (create_payment_link, refund_payment).
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 explains the pull-based nature and that no webhook is needed, giving context for when to use. However, it does not explicitly state when not to use or mention prerequisites beyond the parameter.
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?
Adds behavioral context beyond annotations by noting that refunds respect owner policy guardrails (x-agentpay-max-amount) and that the amount is checked before gateway interaction. Annotations already indicate destructiveHint=true.
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 purpose and default behavior, second adds critical constraint. No unnecessary words.
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?
Covers purpose, usage, parameters, and policy constraints. Lacks return value info, but given no output schema and simple tool, it is adequate.
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 (100% coverage). Description clarifies the amount parameter's role in partial vs full refund, adding semantic value beyond 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?
Clearly states 'Refund a paid payment (created by create_payment_link)' with a specific verb and resource, distinguishing it from siblings like create_payment_link and query_payment_status.
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?
Explains default full refund and optional partial refund with 'pass amount for a partial refund where supported'. Does not explicitly state when not to use, but 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!