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BizVerify

BizVerify MCP Server

Official
by BizVerify

Purchase Credits

purchase_credits

Create a Stripe checkout session to purchase credits. Select a package (100-10000 credits) and get a payment URL; credits are added after successful payment.

Instructions

Starts a credit purchase: creates a Stripe checkout session for the chosen package and returns a payment URL to present to the user. Does NOT charge immediately and does NOT add credits until the user completes payment — credits are then added automatically. Requires authentication. Packages: credits_100, credits_500, credits_2000, credits_10000 (see get_config for current prices).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
package_idYesCredit package to purchase: credits_100, credits_500, credits_2000, or credits_10000

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description goes beyond the annotations by explaining that the tool does NOT charge immediately, does NOT add credits until payment completion, and that credits are added automatically. It also notes the requirement for authentication. These details are critical for understanding the asynchronous, external behavior (Stripe) not fully conveyed by the openWorldHint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core action and followed by important caveats and the package list. It is compact, well-ordered, and contains no filler, making it efficient for an agent to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the single parameter, no output schema, and the absence of nested objects, the description covers the essential behavior: it creates a checkout session, returns a payment URL, explains the deferred charging/crediting, and states the authentication requirement. This is sufficiently complete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already fully documents package_id with an enum and a sentence listing the options (100% schema description coverage). The description adds the note to see get_config for current prices, which helps the agent select an appropriate package based on pricing, a useful semantic addition beyond the raw enum.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a Stripe checkout session for a credit package and returns a payment URL. It specifies the exact action ('creates'), the resource ('Stripe checkout session'), and the purpose ('start a credit purchase'), which distinguishes it from the sibling read/search tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description indicates when to use it (to start a credit purchase) and directs the agent to see get_config for current prices, implying a prerequisite. It does not explicitly exclude non-purchase uses, but the sibling list contains no other purchasing tool, so the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.