List x402 merchants that have been VERIFIED to accept payment — each one actually paid with real USDC on Base, with the settlement transaction hash. This is different from a liveness probe: public censuses only check whether a 402 is emitted, not whether paying works. Use this to find endpoints that will actually serve you. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it discloses useful behavior: verification means a real USDC payment on Base with a settlement transaction hash, not just a 402 emission. It also notes the tool is free, but it does not describe response format, pagination, or freshness.
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 concise and front-loaded with the core action and verification criterion. The liveness contrast, use-case sentence, and 'Free' signal each add distinct value without unnecessary length.
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 zero-parameter free list call, the description covers what is returned (verified merchants and settlement transaction hashes) and why to use it. It does not specify the exact output schema, but that is a minor gap given the simplicity of the call.
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 has zero parameters, so there is nothing for the description to add beyond the schema. This matches the baseline 4 for a no-parameter 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 a specific action ('List') and resource ('x402 merchants that have been VERIFIED to accept payment'), and explicitly contrasts with liveness probes. This lets an agent distinguish it from siblings like x402_check_endpoint without opening anything else.
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?
It gives an explicit use case: 'Use this to find endpoints that will actually serve you.' It also states what it is not for — liveness checks that only verify whether a 402 is emitted — so the agent knows when to choose an alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct aspect of the x402 ecosystem: endpoint liveness, deep merchant audit, facilitator comparison, gas pricing, market analytics, and verified merchant listings. There is no real overlap between tools.
All tools share the x402_ prefix and snake_case, but only audit_merchant and check_endpoint follow a verb_noun pattern. The remaining tools are noun phrases like gas_price, market_stats, and verified_merchants, making the naming conventions mixed yet still readable.
Six tools is well-scoped for an ecosystem intelligence server. Each tool fills a distinct niche and none feel redundant or superfluous.
The tool set covers the entire discovery and research workflow for the x402 economy: checking endpoints, finding verified merchants, auditing merchant trustworthiness, choosing facilitators, estimating gas costs, and assessing market viability. No obvious dead ends or critical gaps.