@agirails/mcp-server

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agirails_accept_quote

Accepts a provider quote by locking USDC in escrow, transitioning a transaction from QUOTED to COMMITTED. Generates a TypeScript snippet using the transaction ID and agreed price.

Instructions

Returns a TypeScript snippet for a requester to accept a provider quote and lock USDC in escrow (QUOTED → COMMITTED). Requires txId and quotedPrice (agreed USDC amount to lock). Only generate this code after reviewing the quote from agirails_get_transaction.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "txId": "<txId>",
      "quotedPrice": "<quotedPrice>"
    },
    "name": "agirails_accept_quote"
  }
}

Input Schema

Name	Required	Description	Default
`txId`	Yes	Transaction ID returned by agirails_request_service or agirails_list_transactions
`quotedPrice`	Yes	The quoted price in USDC to accept (e.g. "3.00")
`network`	No		testnet

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0May 30, 2026

TDQS

A3.8/5.0

Behavior2/5

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

The description claims to return a TypeScript snippet (code generation) but also says 'accept a provider quote and lock USDC in escrow', which implies performing an on-chain action. This ambiguity about side effects (code generation vs. actual execution) is misleading. Annotations do not clarify; readOnlyHint=false and destructiveHint=false are consistent with code generation but inconsistent with actual locking.

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?

Two sentences efficiently convey purpose and usage condition without extraneous detail. Every sentence earns its place.

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?

Given the tool has 3 parameters, no output schema, and minimal annotations, the description covers purpose, required parameters, and a usage condition. It lacks clarity on whether the tool actually executes an action or just generates code, which is a notable gap. Otherwise adequate.

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?

The description mentions txId and quotedPrice are required and adds context that quotedPrice is the agreed USDC amount. However, the schema already describes these parameters adequately (coverage 67% per context signals). The description adds marginal value beyond the schema.

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 it returns a TypeScript snippet to accept a provider quote and lock USDC in escrow, with a state transition from QUOTED to COMMITTED. This distinguishes it from siblings like agirails_submit_quote (provider side) and agirails_get_transaction (viewing).

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 explicitly says 'Only generate this code after reviewing the quote from agirails_get_transaction', providing a clear when-to-use guideline. Could be improved by also stating when not to use, but the guidance is specific and actionable.

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