Discover and quote x402-paid Base intelligence products.
Scored across 2 tools
The two tools are clearly distinct: list_products provides an overview of all products, while quote_token_product focuses on a single product's quoting and purchase URL. There is no overlap in their purposes, making selection unambiguous.
Both tool names follow the same verb_noun pattern: list_products and quote_token_product. The naming is consistent and predictable, with clear verbs and nouns.
With only two tools, the server feels minimal. While it may cover a narrow scope (listing and quoting), it is borderline for a typical MCP server, which often includes more operations. The count is not excessive but is on the low end.
The tools cover the core read and quote operations for products, but there is no tool for actual purchase execution (though the quote returns a purchase URL). Minor gaps exist, such as lack of product detail retrieval beyond the list, but the surface is sufficient for its apparent purpose.
List Prime-Agent x402 products, prices, capabilities, and purchase URL templates.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'List' and names the data included; it does not explicitly state that the operation is read-only, describe the response format, or mention any limits or error behavior. The lack of explicit safety cues is a notable gap for a tool without annotation support.
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 with no filler words. It immediately states the action and resource, then lists the included data. Every word contributes meaning.
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 tool is simple with no parameters, so the description covers the main purpose adequately. However, since there is no output schema and no annotation, the description does not specify the exact response shape or whether results come as an array, paginated, etc. It lists the conceptual data but leaves structural ambiguities.
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 the description does not need to explain parameter meaning. The schema coverage is 100% (empty schema), and the description adds no parameter-related value, but none is needed given the absence of parameters.
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 uses the specific verb 'List' with a clear resource ('Prime-Agent x402 products') and enumerates the output contents (prices, capabilities, purchase URL templates). It is clear but does not explicitly contrast with the sibling tool quote_token_product; the distinction is only implicit in the verb choice.
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 is provided about when to use this tool versus quote_token_product. The description simply states what the tool does and offers no context or exclusions, leaving the agent to infer the appropriate use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Quote one product and return the exact x402 purchase URL without spending funds.
| Name | Required | Description | Default |
|---|---|---|---|
| address | No | ||
| product | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden. It does disclose the most important behavioral trait: the operation does not spend funds. Missing are details about whether the optional address affects the quote, whether any network call occurs, or whether the returned URL expires.
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 well-structured sentence with no filler. The verb, resource, output, and safety qualifier are all front-loaded and each phrase adds value.
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?
There is no output schema and no annotations, so the description must provide context on its own. It covers the core purpose and return value, but leaves the address parameter and the relationship to list_products unexplained. For a simple 2-parameter tool this is adequate but still has clear gaps.
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%, so the description must compensate. It clarifies that 'product' is the item being quoted, but it gives no meaning to the 'address' parameter, which is nullable and optional. The agent would have no way to know what address should contain.
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 uses a concrete verb (quote), identifies the resource (one product), and states the result (exact x402 purchase URL). It also adds the 'without spending funds' qualifier, which clearly separates it from purchase/execution tools and from the sibling list_products.
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 implied rather than explicit: the 'without spending funds' phrasing suggests using this tool when a quote or pre-payment URL is needed. However, it never names list_products, states when not to use this tool, or explains the choice between browsing products and quoting one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
list_productsquote_token_productDiscover, quote & invoke RocketCore x402-paid cyber/market intelligence products.
Find and quote agent capabilities, then pay only the selected x402 execution URL.
Discover x402 paid APIs and inspect fresh payment requirements before authorizing spend.
Instant x402 spend-cap pack for agents. get_quote then buy_intel_pack 5 USDC Base. No human.
Add one secure layer between your agents and this server.
