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agentpay — card-funded wallets for AI agents

Pay-per-call LLM

chat

Pay-per-call LLM, no API key. Sends messages to Fuse chat completions; agentpay settles the standard x402 v2 BSV 402 from this wallet and returns the completion plus receiptUrl and txid. Models: fuse-fast (500 sats) or fuse-smart (2500 sats). Wallet limits, scoped keys, and trial budgets apply. Pass dryRun to quote without spending.

Input Schema

NameRequiredDescriptionDefault
keyNoAgent key (agp_…). Optional when the MCP connection sends Authorization: Bearer.
refNo
modelNoFuse model (default fuse-fast). fuse-fast = 500 sats, fuse-smart = 2500 sats.
dryRunNoQuote + policy check only, no debit or settlement
messagesYesOpenAI-style chat messages
approvalIdNoApproval id from a prior approval_required response
max_tokensNo
amountCentsNoOverride the USD cents charged (min 1 cent default)
descriptionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and largely meets it: it discloses that a real payment settles from the wallet, that wallet limits/scoped keys/trial budgets apply, that dryRun avoids any debit, and that the response includes completion, receiptUrl and txid. It stops short of covering reversibility, approval gating, or failure/rate behavior.

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

Conciseness4/5

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

Front-loads the core value proposition (pay-per-call, no API key) then flows through mechanism, prices, constraints, and the dryRun escape hatch in tight, information-dense sentences. Every clause earns its place, though it is on the denser end.

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

Completeness4/5

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

For a 9-param paid tool with no annotations and no output schema, the description is close to complete: it explains cost, side effects, safe mode, and — critically — the return shape (completion plus receiptUrl and txid) that no output schema supplies. The missing piece is the approval/approvalId path and error behavior.

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

Parameters3/5

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

Schema coverage is 67%, so most parameters are documented in the schema already. The description reinforces model pricing and dryRun semantics but adds no syntax or meaning for undocumented params like ref, approvalId, max_tokens, and amountCents — notably it never explains the approval flow implied by approvalId. Baseline 3 fits.

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

Purpose4/5

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

States a specific verb and resource ("sends messages to Fuse chat completions") and pins the tool's effect (agentpay settles the x402 v2 BSV 402 and returns completion). It reads clearly as a paid chat-completion call, distinguishing it from generic siblings. It stops short of explicitly contrasting with payment siblings like pay_service or spend, which also spend wallet funds.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: the dryRun tip implies a quote-before-spend workflow, and the pricing note implies cost tradeoffs. But nothing says when to prefer this over pay_service/spend, and no prerequisites (auth, approval flow) are laid out as a when-to-use rule. Adequate but with clear gaps.

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

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