run.pay
Server Details
Stripe-native marketplace where AI agents discover and pay per call for API services.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- PalabreX/runpay-mcp
- GitHub Stars
- 1
- Server Listing
- runpay-marketplace
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 2.7/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one lists available services, the other calls a service and processes payment. There is no overlap or ambiguity.
Both tools follow a consistent verb_noun pattern: list_services and call_service. The naming convention is uniform and predictable.
With only two tools, the server feels minimal for a marketplace and payment service. While it covers basic listing and purchase, more tools (e.g., for service details, cancellations) would be expected.
The tool surface has significant gaps: there is no way to view service details beyond listing, no cancellation, no user account management, and no means to handle errors or refunds. Essential lifecycle operations are missing.
Available Tools
2 toolscall_serviceCInspect
Call a service and pay automatically via Stripe per use
| Name | Required | Description | Default |
|---|---|---|---|
| payload | Yes | ||
| agent_id | Yes | ||
| service_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It discloses automatic payment per use but lacks details on failure handling, response format, or side effects. Critical behavioral traits like what happens if payment fails or if the service is not found are missing.
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 a single, front-loaded sentence, which is efficient. However, it sacrifices necessary detail in favor of brevity. For a tool with three parameters and complex behavior, slightly more length would be justified.
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 the tool has three required parameters (one a nested object) and no output schema, the description is insufficiently complete. It does not clarify the payload structure, expected input formats, or any return values, leaving the agent without essential context for correct usage.
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 description coverage is 0%, and the description adds no meaning to the parameters. It does not explain what 'payload' should contain, the role of 'agent_id', or how 'service_id' is used. With three required parameters, this is a major gap for an agent to correctly invoke the tool.
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 states 'Call a service and pay automatically via Stripe per use,' which clearly indicates the tool's primary action (calling a service) and its key feature (automatic payment). It distinguishes itself from the sibling tool 'list_services' by focusing on execution rather than listing.
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 implies usage for services requiring payment, but it does not explicitly state when to use this tool versus alternatives like list_services. There is no guidance on prerequisites or scenarios where this tool should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_servicesCInspect
List all available services for purchase on run.pay marketplace
| Name | Required | Description | Default |
|---|---|---|---|
| search | No | ||
| category | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states 'List all available services' with no mention of authentication, pagination, rate limits, or side effects. This is insufficient for a marketplace listing tool.
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 a single sentence, which is concise but lacking any structure. It could be improved by front-loading key info or adding brief parameter details.
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 and simple parameters, the description fails to mention pagination, sorting, filtering behavior, or return format. For a listing endpoint, this is incomplete.
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 description coverage is 0%, and the description does not explain the two parameters (search, category). Their purpose is entirely inferred from schema field names, adding no value beyond the raw 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 action (List) and resource (services) with context (run.pay marketplace). It distinguishes from the sibling tool 'call_service' by indicating this is for browsing/purchase listing, though not explicitly.
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?
No guidance on when to use this tool versus the sibling 'call_service'. The description does not specify prerequisites or contexts where this tool is appropriate.
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
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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.
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