PayperWork
Server Details
Index of PayperWork's pay-per-call services for agents over x402: lists and describes them. Free.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 2 tools
list_services and describe_service have clearly distinct purposes: one enumerates the catalog, the other returns full details for a single service. There is no meaningful overlap that would cause misselection.
Both tools follow a consistent verb_noun snake_case pattern: list_services and describe_service. The convention is predictable and readable.
With only two tools, the surface feels thin even for a read-only service catalog. It is functional but leaves little room for filtering, searching, or richer discovery workflows.
For a service directory, list and describe cover the core read/discovery lifecycle and provide endpoints, routes, prices, and limits. Minor gaps such as search or filtering are workable through list_services plus describe_service.
Available Tools
2 toolsdescribe_serviceDescribe a serviceARead-onlyInspect
One service in full: its MCP URL and config snippet, HTTP routes, prices, limits and security model. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| service | Yes | drop, ai, decide or image |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
readOnlyHint=true already tells the agent this is a safe read, so the lower bar applies. The description still adds real value by disclosing that the call is 'Free' (no cost/credit consumed) and by enumerating exactly which fields constitute the 'full' payload, which the annotation cannot convey.
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?
One sentence, front-loaded with the resource and its scope, then the returned fields, then the cost caveat. Every clause carries information; nothing is padded or repeated from the name.
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?
For a one-parameter read tool with no output schema, the description is sufficient: it enumerates the return contents thoroughly and states that the call is free, which is the main behavioral fact an agent needs before invoking it.
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 100% and the single parameter is a closed enum of four service names, so the schema already does the work. The description never mentions the 'service' argument or how to choose among drop/ai/decide/image, so it adds nothing beyond the schema — baseline 3.
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?
'One service in full' plus an explicit enumeration of what comes back (MCP URL, config snippet, HTTP routes, prices, limits, security model) makes the tool unmistakably a single-service detail fetch. It implicitly contrasts with list_services via 'one service ... in full', but never names the sibling, so it stops short of a 5.
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?
Usage is only implied: an agent can infer 'call this when you need details on one specific service.' There is no explicit when/when-not statement and list_services is never mentioned as the alternative for discovery, so routing between the two is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_servicesList servicesBRead-onlyInspect
The PayperWork services with their MCP endpoints, HTTP routes, prices and limits. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so safety is covered by structured data. The description adds that the call is free, which is useful behavioral context, but says nothing about result size, ordering, or whether it returns all services or a subset.
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?
A single compact sentence, front-loaded with the resource and content it returns. The trailing 'Free.' is a terse fragment but carries real information an agent would otherwise lack.
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?
With no output schema, the description carries the burden of explaining return values; it names the fields loosely but does not indicate the shape (array of service objects), volume, or how to drill into one service. Adequate but thin for a catalog-listing tool.
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 tool takes zero parameters, so there is no parameter semantics to document; the baseline for 0-param tools applies. No misleading parameter claims are made.
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 names the resource and the payload contents (MCP endpoints, HTTP routes, prices, limits), so an agent can infer this returns a service catalog. However, it is a noun-phrase fragment with no explicit verb and no differentiation from the sibling describe_service, leaving the exact action implicit.
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?
There is no statement of when to use this versus describe_service, and no preconditions (auth, pagination, filtering). The only contextual hint is 'Free.', which addresses cost but not selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- Changed
describe_service2 fields changed- changed
Input schema / properties / service / descriptionPrevious value: -"drop, ai or decide"New value: +"drop, ai, decide or image" - changed
Input schema / properties / service / enumPrevious value: -[ - "drop", - "ai", - "decide" -]New value: +[ + "drop", + "ai", + "decide", + "image" +]
1 tool update
- Changed
describe_service2 fields changed- changed
Input schema / properties / service / descriptionPrevious value: -"drop or ai"New value: +"drop, ai or decide" - changed
Input schema / properties / service / enumPrevious value: -[ - "drop", - "ai" -]New value: +[ + "drop", + "ai", + "decide" +]
6 tool updates
- Removed
delete - Added
describe_service - Removed
get - Removed
list - Removed
put - Removed
wait
6 tool updates
- First observed
delete - First observed
get - First observed
list - First observed
list_services - First observed
put - First observed
wait
Related MCP Connectors
Agent-payable web data over x402: 18 keyless services an agent pays per call.
Pay-per-call APIs for agents: text analysis, game facts, translation QA, hook scoring via x402.
Agent trust, pre-purchase risk, deliverable checks, data and SEO tools. Pay per call via x402.
129 pay-per-call agent tools: security, threat intelligence, web search and SEO data tools. x402
Related MCP Servers
- AlicenseAqualityBmaintenanceVerified pay-per-call catalog: factual checks of x402 agent services for AI agents.31MIT
- AlicenseNot gradedqualityDmaintenanceProvides 25 pay-per-call tools from agents.oromi.co.uk (business, property, verification, web, crypto) into MCP-capable models, with quote mode for browsing and paid mode using x402.75 npmMIT

Cinderwrightofficial
AlicenseBqualityCmaintenancex402 Discovery Hub. Search engine for the agent economy with 1450+ services indexed. Search by keyword, browse by category, free service submission.1237 npm4MIT- AlicenseAqualityAmaintenanceProvides a catalog of paid micro-work tools for text processing, speech, and image generation with fixed USDC pricing via x402. Enables agents to discover capabilities, get quotes, and prepare calls without handling wallet keys.3MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.