Philippines Payments (PayMongo — GCash / Maya / cards)
Server Details
Philippines payments for AI agents — GCash, Maya, cards via PayMongo. 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 4.5/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one creates a payment link, the other queries payment status. There is no overlap or ambiguity.
Both tool names follow a consistent verb_noun pattern (create_payment_link, query_payment_status), making them predictable and easy to understand.
With only 2 tools, the server is very minimal. While it covers the essential create and query operations, it feels thin for a comprehensive payment service.
The server covers the core workflow of creating a payment link and checking status. However, it lacks tools for cancelling, listing, or managing payment links, which are minor gaps for a basic service.
Available Tools
2 toolscreate_payment_linkAInspect
Create a Philippines payment link in PHP via PayMongo, a leading Filipino payment gateway. Buyer pays with GCash, Maya (PayMaya), credit/debit card, GrabPay, QR Ph, or online banking — restrict with payment_method_types (default ["card","gcash"]; only methods activated on the merchant account work). Returns a hosted checkout URL the buyer opens to pay — payment completes automatically, no confirm step. Amounts in PHP pesos (decimals allowed, e.g. 499.50; minimum ₱20). Bring your own PayMongo secret key via the x-paymongo-secret-key header (free sk_test_ keys from dashboard.paymongo.com; test keys never move real money). Money always flows buyer→PayMongo→merchant; this service never touches funds.
| Name | Required | Description | Default |
|---|---|---|---|
| provider | No | Which gateway. Omit to auto-select: Xendit when x-xendit-secret-key header is present, otherwise PayMongo. payment_method_types applies to PayMongo only. | |
| amount_php | Yes | Amount in PHP pesos (e.g. 499.50; converted to centavos internally). Minimum ₱20. | |
| cancel_url | No | Optional https URL if the buyer cancels. | |
| description | Yes | What this payment is for (shown to the buyer, ≤255 chars) | |
| success_url | No | Optional https URL to send the buyer to after successful payment. | |
| payment_method_types | No | Payment methods to offer. Default ["card","gcash"]. Common values: card, gcash, paymaya, grab_pay, dob, dob_ubp, brankas_bdo, brankas_landbank, brankas_metrobank, atome, billease, qrph. Only methods activated on the merchant PayMongo account are accepted. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses important behavioral traits: payment completes automatically (no confirm step), money flows buyer→PayMongo→merchant, this service never touches funds, and requires an API key via header. Annotations indicate mutation but no destruction, which aligns with the description. No contradictions.
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 thorough but not overly verbose. It is front-loaded with the core purpose, and each sentence adds meaningful context. Minor redundancy could be trimmed, but overall it's well-structured and efficient for an AI agent.
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 covers all key aspects: purpose, payment methods, amount constraints, gateway selection, API key requirement, test key usage, and the returned checkout URL. Even without an output schema, the description explains the return value sufficiently. It is complete for the tool's complexity.
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% with all parameters described. The description adds extra value by explaining amount constraints (PHP, decimals, minimum ₱20), listing common payment method values, and detailing provider auto-selection logic. The description complements the schema well.
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 Philippines payment link in PHP via PayMongo'. It specifies the verb (create), resource (payment link), and scope (Philippines, PHP, via PayMongo). It distinguishes from the sibling tool 'query_payment_status' by being a creation tool.
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 context on when to use the tool: to create a payment link for Philippine payments. It mentions alternative gateways via the 'provider' parameter and hints at using 'query_payment_status' for status checks. It could be more explicit about when not to use it, but the information is mostly adequate.
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 Philippines checkout session (created by create_payment_link) has been paid. Fetches the session from PayMongo directly — a reliable pull-based alternative to webhooks. paid=true when a payment with status paid exists (result status PAID; otherwise ACTIVE / EXPIRED).
| Name | Required | Description | Default |
|---|---|---|---|
| provider | No | Omit to auto-select by credential headers. | |
| session_id | Yes | The session_id returned by create_payment_link (PayMongo cs_... or Xendit reference) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds value by explaining the source (PayMongo directly) and the meaning of the result statuses (PAID, ACTIVE, EXPIRED), providing 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, front-loaded with purpose, no unnecessary words. Every sentence provides useful context.
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 no output schema, the description sufficiently explains the return value (paid=true/false and statuses). It could mention that it only works for Philippines checkout sessions, but the tool name already implies regional scope.
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% and already describes parameters. The description adds semantic value by clarifying that session_id is returned by create_payment_link, and that provider auto-selects based on credential headers, which reinforces the schema without redundancy.
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 whether a Philippines checkout session has been paid, specifying the resource (checkout session) and action (check payment status). It also implicitly distinguishes from its only sibling, create_payment_link, which is about creating a session.
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 on when to use this tool: as a reliable pull-based alternative to webhooks. It does not explicitly state when not to use it, but the context is clear enough for an agent to select it appropriately.
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!