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AgentWorld MCP Server

AgentWorld MCP Server

by shawnhvac
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_recent_settlements

Verify x402 USDC settlement receipts by fetching the last five AgentPay Base L2 transactions with hashes, timestamps, amounts, explorer links, lifetime count, and a live/idle freshness check.

Instructions

[FREE] Settlement receipt verifier: the last 5 x402 USDC settlements from the AgentPay facilitator on Base L2, each with tx hash, timestamp, amount and a basescan explorer link, plus the lifetime settled count and a live/idle freshness verdict.

Real receipts from on-chain settlements - cryptographic proof the facilitator settles, not a marketing claim. Agents can poll this before paying to confirm the rail is live. Payer identity stays private.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_recent_settlements"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations supplied, the description carries the full disclosure burden and does reasonably well: it declares the tool is free, read-only verification, returns exactly the last 5 records, draws from on-chain Base L2 data, and explicitly states payer identity stays private — a privacy trait not inferable from any structured field. It omits rate limits, caching/freshness semantics beyond the

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-loaded with the

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?

With no output schema and no annotations, the description must explain what comes back — and it does, enumerating tx hash, timestamp, amount, basescan explorer link, lifetime settled count, and a live/idle freshness verdict. For a zero-parameter read tool, nothing an agent needs in order to call it or interpret the result is missing.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly implies calling it requires no inputs (it is polled as-is), which is consistent with the empty schema and additionalProperties=false.

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 (

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?

Gives an explicit trigger:

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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